Abstract

The present invention is directed to the identification of a biomarker specifically located in the plasma membrane of pancreatic beta cells. Based on a set of specific features the biomarker is a unique candidate for imaging and targeting strategies to study the pancreatic beta cell mass in health and disease (T1D, T2D, pancreatic cancers, obesity, islet transplantation, beta cell regeneration).

Description

A NEW BIOMARKER EXPRESSED IN PANCREATIC BETA CELLS USEFUL IN IMAGING OR TARGETING BETA CELLS

FIELD OF THE INVENTION

The present invention is directed to the medical field, in particular to the imaging and quantification of pancreatic beta cell mass, targeting or visualization of pancreatic beta cells for pathology and/or follow up of diabetic disorders, follow up of islet transplantation and to purification strategies of pancreatic beta cells.

BACKGROUND OF THE INVENTION

Diabetes is caused by insufficient production of insulin, the key hormone responsible for controlling blood glucose levels. Insulin is produced by beta cells located in the islets of Langerhans, clusters of endocrine cells diffusely distributed throughout the pancreas. Medical textbooks define type 1 diabetes (T1 D) as a result of a progressive and eventually complete loss of beta cell mass following autoimmune destruction, whereas type 2 diabetes (T2D) is described as being caused by insulin resistance in peripheral tissues, that is not adequately compensated for by the pancreatic beta cells, that is more prevalent in obese patients, leading to progressive beta cell failure (and eventually death), at least in part due to chronic metabolic stress. The standard treatment for T1 D has been multiple daily injections of insulin to control blood glucose levels in the patient. In T2D, however, (initial) therapy is lifestyle changes (weight loss and exercise), often in combination with drugs stimulating release of endogenous insulin and/or increase peripheral insulin sensitivity, with addition of insulin if needed. Emerging and exciting evidence, however, suggests that the dogma that in longstanding T1 D all beta cells are destroyed and the pancreas cannot produce insulin, is probably wrong for many of the patients. As initially suggested by work performed in non-obese diabetic (NOD) mice (Strandell, E. et al. (1990) J. Clin. Invest. 85, 1944-1950), and in islets isolated from T1 D patients (Marchetti, P. et al. (2000) Diabetes Care 23, 701-703), a population of functionally suppressed but still alive beta cells remains. These cells are able to produce and secrete small amounts of insulin, as shown by measuring C-peptide and, most importantly, they may survive for decades after the diagnosis of T1 D (Keenan, H.A. et al. (2010) Diabetes 59, 2846-2853; Oram, R.A. et al. (2014) Diabetologia 57, 187-191 ; Couri, C.E. et al. (2009) JAMA 301 , 1573-1579). These new findings require a big conceptual change in how we understand
T1 D and, although they have been initally perceived with disbelief by many scientists (Faustmann, D.L. (2014) Diabetologia 57, 1-3), they open new avenues towards creating new approaches to tackle an old problem.

Currently, the natural history of beta cell loss in T1 D and T2D and the relationship between (anatomical) beta cell mass and function in the course of diabetes is not clear. For T2D patients, for example, it has been demonstrated that beta cell function may deteriorate, whereas beta cell mass is preserved. Another level of complication is that there are marked (>fivefold) interindividual differences in beta cell mass (Meier, J.J. et al. (2009) Diabetes 58, 1595-1603; Rahier, J. et al. (2008) Diabetes Obes. Metab. 10 (Suppl. 4), 32-42), with a large overlap between non-diabetic individuals and patients with impaired glucose tolerance/overt diabetes (Ritzel, R.A. et al. (2006) Diabetes Care 29, 717-718). Individual T2D patients have a diverse pathophysiology and differ in the progression of the disease. It is presently not possible to predict individually which T2D patients will eventually need insulin therapy. T1 D patients may have remaining beta cells decades after the onset of disease, and we do not know how these residual beta cells influence the course of the disease: do they help to stabilize blood glucose levels, reduce the rate of diabetes complications, or prevent hypoglycemia? It is crucial to underline that clinical diabetes depends not only on the absolute amount of beta cells but also on the function of the individual beta cells. Patients with diabetes or impaired glucose tolerance tend to have a lower beta cell mass, but beta cell mass by itself does not necessarily predict the glucose tolerance of individual patients. Knowledge about the beta cell mass in relation to its function may help to predict individually who will develop diabetes and who will respond or not to particular therapies. So far, all human studies to determine beta cell mass have been carried out on pancreatic specimens obtained by pancreatectomy or from autopsies, whereas beta cell function is assessed non-invasively by glucose tolerance testing or clamping. A challenge for histological determination of beta cell mass in tissue specimens is that beta cells may be viable but non-functional (Coppieters, K.T. et al. (2012) J. Exp. Med. 209, 51-60), in other words degranulated and/or not releasing insulin, such that they may be missed when anti-insulin staining is used for immunohistochemical determination of beta cell mass - meaning that the true beta cell mass is underestimated (Marselli, L. et al. (2014) Diabetologia 57, 362-365). In addition, beta cells may be detected as insulin-positive even though they may be unable to release the hormone in vivo. It is therefore clear that non-invasive methods for determining beta cell mass are warranted, such as non-invasive imaging methods or blood biomarkers. These methods, analyzed in parallel with C-peptide release, would ideally allow the detection of both functional beta cells (beta cell mass and stimulated C-peptide are in agreement) and non-
functional beta cells (beta cells are present, but there is no or very low stimulated C- peptide release). This would enable in-dependence from tissue specimens, with their inherent limitations, and would open a window of opportunity for cross-sectional as well as longitudinal clinical studies in large numbers of patients. Beta cell mass and function are not equivalent - determination of individual beta cell function and mass may therefore be a cornerstone of future individualized treatment and prevention of diabetes. Knowing the remaining beta cell mass in diabetic patients or in individuals at risk of developing the disease, and linking this information to the evaluation of beta cell function in longitudinal studies, would massively improve our understanding of the pathophysiology and natural history of diabetes. This knowledge is also expected to enable the development of novel treatment and prevention strategies. So far, few studies have compared the effect of T2D drug treatments on residual beta cell function, often using poor functional measures such as homeostasis model assessment (HOMA). Imaging beta cell mass as compared to function will enable comparative studies between glucose-lowering drugs. It will allow individualization of patient treatment, for example by identifying those individuals with T2D that would benefit from therapies relying on the presence of viable, insulin-secreting beta cells, such as sulfonylureas or glucagon-like peptide-1 (GLP-1 ) analogs, whereas others with limited beta cell reserve may directly change to insulin replacement. In the case of T1 D, the presence of a substantial reserve of non-functional beta cells may indicate the use of anti-inflammatory agents (e.g., cytokine blockers) in parallel to insulin therapy, with the hope of restoring some endogenous insulin release. As stated above, knowing the functional level of the beta cells, in relation to the beta cell mass of an individual might help us to predict better the course of the disease and to define the best approaches individually to prevent, reverse, and treat diabetes.

Currently, attempts at in vivo visualization of beta cells in humans rely on radiolabeled tracer molecules that bind to beta cells with high specificity. These radiotracers can be detected in the picomolar range by positron emission tomography (PET) and single photon emission computed tomography (SPECT). Although the spatial resolution of both types of scanners does not allow single islets to be resolved, the signal detected in the pancreas is highly specific when the radiotracers specifically bind to beta cells (Andralojc, K. et al. (2012) Diabetologia 55, 1247-1257). Currently, three radiotracers are undergoing early clinical evaluation: 18F-dihydro-tetrabenazine (DTBZ) for imaging of vesicular monoamine transporter 2 (VMAT2), 11C-hydroxytryptophane (HTP) as a marker for the serotonergic system, and 111ln- and 68Ga-labeled exendin targeting the glucagon-like peptide-1 (GLP-1 ) receptor. Although 30% of the DTBZ signal seems to originate from beta cells (the remaining 70% originates from other endocrine cells) (Freeby, M. et al.
(2012) Islets 4, 393-397), and HTP is a marker for the complete endocrine pancreas (i.e., all cells in the islets of Langerhans), exendin is suggested to be specific for beta cells (Brom, M. et al. (2014) Diabetologia http://dx.doi.org/10.1007/ s00125-014-3166-3). Of concern, however, beta cell imaging based on labeled exendin shows only a 50% decrease in beta cell mass in patients with > 15-20 years of T1 D, a stage of the disease where most patients have lost >95% of their beta cells, suggesting lack of sufficient specificity. Discovery of novel beta cell biomarkers, such as for instance specific splice variants present in beta cells only, may improve the potential for radiotracer-based imaging in the future. Although the clinically available radiotracers give us different information, it is intriguing that all three of them show a considerable overlap of the signal detected in the pancreas between healthy individuals and T1 D patients, indicating the presence of residual beta cell mass in T1 D patients and large interindividual variations among healthy individuals. These results are in line with the histology-based findings discussed above, suggesting that currently available imaging methods deliver information about pancreatic beta cell mass. This information, however, is not yet sufficient for accurate follow up of beta cell mass in diabetic patients.

Beta cells constitute 1-3% of the pancreatic mass and are scattered throughout the pancreas in the tiny islets of Langerhans (100-300 micrometer in diameter). The disperse localization of the cells (unlike tumor cells) makes imaging challenging. An additional level of complexity is that, to determine the differences in anatomical beta cell mass between diabetic subjects, all intact islets remaining in later stages of diabetes need to be detectable, thus detection methods must be exquisitely sensitive. Single islets cannot yet be spatially resolved non-invasively in vivo in humans. A highly sensitive method is thus necessary to permit easy quantification of tracer uptake in the endocrine pancreas, without necessarily requiring resolution of single beta cells/islets. Therefore, approaches for clinical beta cell imaging should primarily rely on chemical resolution with high sensitivity (i.e., visualization of beta cells based on high specificity and biochemical/metabolic characteristics of a tracer molecule) by using tracers for positron emission tomography (PET) or single photon emission computed tomography (SPECT), techniques characterized by a very high sensitivity.

Consequently, there is a need for specific and reliable biomarkers for the identification and visualization of beta cells of pancreatic islets of Langerhans, which allow reliable beta cell mass quantification. One of the aims of the present invention is to provide such markers.
SUMMARY OF THE INVENTION

The present invention is directed to a biomarker that is preferentially expressed in in beta- cells. This biomarker is a unique candidate for imaging and targeting strategies to study the pancreatic beta cell mass in health and disease (type 1 diabetes mellitus (T1 D), type 2 diabetes mellitus (T2D), hyperinsulinemia, obesity, neuroendocrine tumors, occurrence of insulinoma or islet transplantation). The biomarker is specific for beta cells and can be used for beta cell targeting and non-invasive in vivo imaging. The use of targeting strategies against these biomarkers will allow early identification of variation in beta cell mass and the follow-up of therapies for diabetes, including islet transplantation, attempts at beta cell regeneration etc..

Imaging/targeting strategies using labeled antibodies, aptamers, interacting proteins, peptides or ligands directed against these biomarkers will allow beta cell specific labeling and visualisation, beta cell mass quantification, evaluate the progression of diabetes/ and will lead to earlier prediction of pancreatic disease state, allow earlier intervention and higher chance to cure or halt diabetes, and enable the follow up of beta cell mass following islet transplantation.

The biomarker of the invention can also be a potential target for autoimmunity in T1 D, as is the case of other abundant beta cell surface proteins, and may thus be a target for autoantibodies or T-cells. Detection of these auto-antibodies and T-cells may allow prediction of T1 D.

Another application of the biomarker as disclosed herein will be the follow-up of beta cell mass in patients with type 1 and type 2 diabetes and following islet transplantation. Beta cell imaging will be also useful as a surrogate marker for clinical trials of new therapies aiming to prevent beta cell mass loss in diabetes or to restore beta cell mass by regeneration. The biomarkers could also be targeted to deliver agents to stop inflammation in the case of T1 D or transplantation. Finally, measurement of the biomarker (RNA or protein) in the circulation may provide indication of ongoing beta cell death in diabetes.

The invention provides the following aspects:

1 . Use of TMEM132D splice variant 1 (referred to herein as "variant 1 ") as a

2. The use according to claim 1 , wherein TMEM132D variant 1 is used for visualising or measuring pancreatic beta cell mass, preferably in vivo and/or in vitro.
The use according to claim 1 , wherein TMEM132D variant 1 is used as a circulation marker for detecting damaged beta-cells in a blood, plasma, serum, or urine sample of a subject, preferably in vivo and/or in vitro.

The use according to any one of aspect 1 to 3, wherein said TMEM132D variant 1 is defined by the sequence of SEQ ID NO: 1.

a) detecting or visualizing the beta cells in a sample of a subject using the method according to aspect 5, and

b) quantifying the amount of labelled beta cells, preferably in vivo and/or in vitro. Use of a binding molecule specifically binding to TMEM132D variant 1 , in the preparation of a composition for the in vitro and/or in-vivo visualisation of pancreatic beta cells; Binding molecule specifically binding to TMEM132D variant 1 , for use in the in-vivo visualisation of pancreatic beta cells; or Use of a binding molecule specifically binding to TMEM132D variant 1 , for the in-vitro visualisation of pancreatic beta cells.

Use of a binding molecule specifically binding to TMEM132D variant 1 , in the preparation of a composition for the in vitro and/or in-vivo diagnosis of pancreatic beta-cell related disorders; Binding molecule specifically binding to TMEM132D variant 1 , for use in the in-vivo diagnosis of pancreatic beta-cell related disorders; or Use of a binding molecule specifically binding to TMEM132D variant 1 , for the in-vitro diagnosis of pancreatic beta-cell related disorders.

A method of in vivo diagnosing a beta-cell-related disorder encompassing the following steps:

a) introducing a labelled molecule, specifically binding to TMEM132D variant 1 , into a subject,
b) visualizing the labelled molecule specifically located to the beta cell population in the pancreas in vivo,

c) quantifying the beta cells mass in said subject,

d) comparing the beta cell mass data obtained in step c) with the beta cell mass of a healthy subject, or of a previous analysis of the same subject.

e) diagnosing the subject as having diabetes or being at risk of having diabetes when the level of beta cell mass obtained in step c) is reduced as compared to that of a healthy subject and diagnosing the subject as having hyperinsulinemia or being at risk of having hyperinsulinemia when the level of beta cell mass obtained in step c) is increased as compared to that of a healthy subject, or of a previous analysis of the same subject.

The method according to aspect 10, wherein said labelled molecule is selected from the group comprising: an antibody or a fragment thereof, a nanobody, an affibody, a minibody, a diabody, a single chain antibody, an aptamer, a

photoaptamer, a peptide, a small molecule, an interacting partner, an isotopically labelled tracer, or a ligand, specifically binding to TMEM132D variant 1 .

The method according to aspect 10 or 1 1 , wherein said labelled molecule is radio- isotopically labelled, or fluorescently labelled. Useful labels are known in the art and some non-limiting examples have been described herein elsewhere.

The method according to any one of aspects 10 to 12, wherein said in vivo visualisation is done using a PET, PET-CT, SPECT or MRI scan, or through fluorescent imaging.

The method of any one of the aspects 10 to 13, wherein the beta-cell-related disorder is type 1 diabetes mellitus, type 2 diabetes mellitus, hyperinsulinemia, obesity, or occurrence of insulinoma.

A labelled molecule, specifically binding to TMEM132D variant 1 , for use in diagnosis of a beta-cell-related disorder in vivo, according to the method of any one of aspects 10 to 14, preferably wherein the beta-cell-related disorder is type 1 diabetes mellitus, type 2 diabetes mellitus, hyperinsulinemia, obesity, or occurrence of insulinoma.

A kit for (use in) visualising beta cells, for (use in) specifically measuring beta cell- mass, for (use in) diagnosing a beta-cell-related disorder, for (use in) detecting beta cell fragments in a blood or urine sample, and/or for (use in) purifying beta cells in a subject comprising a labelled molecule specifically binding to TMEM132D
variant 1 , preferably wherein said binding molecule is an antibody or a fragment thereof, a nanobody, an affibody, a minibody, a diabody, a single chain antibody, an aptamer, a photoaptamer, a peptide, a small molecule, an interacting partner, an isotopically labelled tracer, or a ligand, specifically binding to TMEM132D variant 1.

A method for following up the success of the transplantation of beta cells in a subject comprising the following steps:

a) measuring the amount of beta-cell mass in the subject at one or more time points after transplantation of the subject with beta cells with the method according to aspect 5,

b) determining the success of the transplantation by comparing the beta cell mass in the course of time by evaluating the evolution of beta-cell mass over time. In a preferred embodiment of said aspect, said measuring of the amount of beta-cell mass in the subject comprises the steps of:

i) labelling beta cells in a sample based on presence of variant 1 of TMEM132D, and

ii) detecting or visualising the labelled beta cells. Said method can be carried out in vivo and/or in vitro.

A method for purifying or isolating beta cells from other pancreatic non-beta cells comprising the following steps:

b) isolating the labelled cells from the non-labelled cells through the tag on the beta cells, thereby obtaining a substantially pure beta cell preparation. Preferably said method is carried out in vitro.

A method for identification of regeneration of beta cells comprising the steps of: a) tagging the beta cells with a labelled binding molecule specifically binding to variant 1 of TMEM132D,

b) isolating the labelled cells from the non-labelled cells through the tag on the beta cells, thereby obtaining a substantially pure regenerated beta cell preparation c) performing immunohistochemistry to identify the number of newly regenerated beta cells, and to define the new beta cell mass

the tag on the potential beta stem cells, thereby obtaining a substantially pure beta stem cell preparation. Preferably said method is carried out in vitro. The method of aspect 21 , further comprising the steps of:

c) performing immunohistochemistry to identify the number of beta stem

A method for identifying new tracer molecules that specifically bind beta cells comprising the steps of:

a) contacting the candidate tracer molecule with TMEM132D variant 1 positive cells or cell-lines and measure the interaction between the candidate tracer molecule and the cells;

b) contacting the candidate tracer molecule with TMEM132D variant 1 negative cells or cell-lines and measure the interaction between the candidate tracer molecule and the cells;

c) comparing the interactions between both steps a) and b); and

d) retain these candidate tracer molecules that bind the cells of step a) but not the cells of step b) as beta-cell-mass tracer molecules. Preferably said method is carried out in vitro.

The method of aspect 18, wherein the TMEM132D variant 1 positive cell or cell-line is selected from the group comprising: rodent pancreatic islets, rat INS-1 E cells and the human beta cell line ENDOC-BH1 ; and wherein the TMEM132D variant 1 negative cell-types or cell-lines are PANC-1 or CAPAN-2.

A kit for (use in) identifying new tracer molecules that specifically bind beta cells comprising two cell types or cell-lines, one being a TMEM132D variant 1 positive cell-type or cell-line and one being a TMEM132D variant 1 negative cell-type or cell-line.
26. The kit of aspect 25, wherein the TMEM132D variant 1 positive cell-type or cell-line is selected from the group comprising: rodent pancreatic islets, rat INS-1 E cells the human beta cell line ENDOC-BH1 ; and/or wherein the TMEM132D variant 1 negative cell-types or cell-lines are PANC-1 or CAPAN-2.

27. A method for identifying new tracer molecules that specifically bind beta cells

comprising the steps of:

a) contacting the candidate tracer molecule with a TMEM132D variant 1 molecule and

b) measuring the interaction between the candidate tracer molecule and the TMEM132D variant 1 molecule, wherein these candidate tracer molecules that specifically bind the TMEM132D variant 1 molecule of step a) are retained as beta cell tracer molecules. Preferably said method is carried out in vitro.

28. A binding molecule specifically binding TMEM132D variant 1 , preferably selected from the group comprising: an antibody or a fragment thereof, a nanobody, an affybody, a single chain antibody, an aptamer, a photoaptamer, a peptide, a small molecule, an interacting partner, an isotopically labelled tracer, or a ligand specifically binding to TMEM132D, preferably to variant 1 of TMEM132D. More particularly, said binding molecule is used for diagnosing T1 D, monitoring T1 D disease progression and/or monitoring T1 D disease treatment, or in monitoring beta cell transplants in the skin intramuscular, or in other accessible locations of the subject.

29. A kit comprising binding molecules according to aspect 28.

In some embodiments, said binding molecules are labelled, preferably with a radioisotope, a fluorescent moiety, a chemiluminescent moiety, a bioluminescent moiety, a chemifluorescent moiety or a metal or magnetic moiety. In one embodiment such a kit is an immunochemical detection kit such as an ELISA kit. In another embodiment, said kit comprises radio(isotopically)labelled binding molecules. More particularly, said kit is used for diagnosing T1 D, monitoring T1 D disease progression and/or monitoring T1 D disease treatment, or in monitoring beta cell transplants in the skin intramuscular, or in other accessible locations of the subject.

30. The kit according to aspect 29, wherein said binding molecules are immobilised on a solid support, such as a chip or microchip.
The kit according to aspect 29 or 30, further comprising one or more (micro )fluidic or microvortex-creating channels wherein said binding molecules are immobilised, whereon beta cells and/or beta cell debris can be bound and subsequently detected. More particularly, said kit is used for diagnosing T1 D, monitoring T1 D disease progression and/or monitoring T1 D disease treatment, or in monitoring beta cell transplants in the skin intramuscular, or in other accessible locations of the subject.

The TMEM132D variant 1 biomarker as defined herein is interesting because of its specificity for pancreatic beta cells. Even if some cross-reactivity would exist of the identified binding molecules with other variants of TMEM132D e.g. those present on alpha cells, said binding molecules could be easily used to detect circulating and degrading beta cells and/or beta cell debris in a specific manner since alpha cells are not destroyed in type 1 diabetes and hence will not be detected in circulation. The use of binding molecules specific for TMEM132D expressed on beta cells is important since it will enable the detection of beta cell debris and hence detect beta cell damage during e.g. T1 D.

The invention hence further provides a method of diagnosing T1 D using the binding molecule or kit comprising binding molecules specific for TMEM132D variant 1 as defined herein. In such a method, detection of beta cells and/or beta cell debris in the circulation of a subject is indicative of T1 D disease development. The invention further provides a method of monitoring T1 D disease progression using a kit comprising binding molecules specific for TMEM132D variant 1 as defined herein. In such a method, an increased detection over timed of beta cells and/or beta cell debris in the circulation of the subject is a measure for disease progression.

The invention further provides a method for monitoring T1 D disease treatment using a binding molecule or a kit comprising binding molecules specific for TMEM132D variant 1 as defined herein. In such a method, a decrease in detection of beta cells and/or beta cell debris is a measure for disease improvement and hence of successful treatment.

The invention further provides a method of monitoring beta cell transplants in the skin intramuscular, or in other accessible locations of the subject, using the binding molecule according to aspect 28 or the kit according to any one of aspects 29 to 31 , comprising the detection of the labelled binding molecule(s) specific for beta
cells, preferably fluorescently labelled binding molecules, using non-invasive clinical imaging methods.

36. Use of the binding molecule according to aspect 28, or of the kit according to any one of aspects 25, 26, or 29 to 31 , for delivering therapeutic agents specifically to beta cells, with the goal of protecting these cells against dysfunction and death in diabetes.

BRIEF DESCRIPTION OF THE DRAWINGS

Figure 1. Strategy used for the discovery of new biomarkers. An lllumina RNA-seq analysis was performed on five human islet samples under control condition, cytokine treatment and palmitate treatment. The data were compared with RNA-seq data from the lllumina Human Body Map containing 5 tissues. A new list of candidate genes was obtained from which TMEM132D was selected for further study.

Figure 3: Expression of TMEM132D variant 1 in different human tissues, cell lines and human islets (HI). Real-time PCR was used for measuring the expression of TMEM132D in different samples. Three different human islet preparations were used for the analysis.

Figure 4: Immunohistochemistry in mouse pancreas using anti-TMEM132D antibody. The darker grey staining (cf. white circles) represents the TMEM-132D variant 1 staining, the darker dots in the tissue are the nuclei of the cells.

Figure 5: Immunofluorescence of TMEM132D in rat pancreas. Staining of Insulin, Glucagon, TMEM132D and Hoechst DNA staining is shown in the same tissue section. Figure 6: Immunofluoresecence of TMEM132D in human pancreas. Staining of Insulin and TMEM132D is shown in the same tissue section and show overlap.

The present invention is directed to biomarkers specifically useful for visualizing pancreatic beta cells.
Said biomarkers are not only specific for pancreatic islets versus exocrine tissue but a number of extra selection criteria were added which makes these biomarker candidates more suitable for the use in beta cell imaging and targeting. Unique datasets were used containing quantitative information (instead of comparative information) to select the biomarker. The unique features assigned to the selected biomarkers are:

1 . The selected biomarker candidate is enriched more than 50-100 times in human islets versus total human pancreas: Instead of using comparative data obtained by microarray, we have quantitative data obtained by RNA sequencing. Since islets constitute 1 -2% of the total pancreas, we used as selection criteria an enrichment of 50-100 times in islets versus pancreas. Using the quantitative data we can calculate how many times the expression will be enriched in human pancreatic islets versus the surrounding human tissues (stomach, spleen, intestine) or versus tissues used for placing islet grafts (liver, kidney) based on comparison with publicly available human RNA-seq datasets; this is a very useful criteria for anticipating background levels and for selecting islet specific candidates. The enrichment in islets versus total pancreas is preferably higher than 50 fold.

2. Selected candidate is enriched in purified rat beta cells compared to purified rat non beta cells making them relatively beta cell specific. The islet composition changes during the evolution of T1 D due to loss of beta cells and the relative increase in non beta cells (mostly alpha cells). It is thus crucial for quantification of beta cell mass that putative biomarkers are specifically expressed in beta cells. The present selection was done based on our unique data set obtained with RNA-seq. Until now no such selection has been done. The term "enriched" means that a higher level of expression is obtained in beta cells when compared to non-beta cells, manipulated under identical conditions. As this analysis is done based on RNA-seq, the FC change is not taken in account so we selected genes that were higher expressed in beta cells than in non-beta cells but no FC criteria was set as such.

3. The selected biomarker is well expressed in beta cells. For imaging the targets need to be expressed in sufficient amount on the pancreatic beta cells to enable detection. We have both quantitative data in human islets and comparative data in human islets and primary rat beta cells to check this criterion.

4. The selected biomarker is located in the plasma membrane and can be used for targeting with specific antibodies, chemical synthesis, natural compounds or with peptides. Antibodies and peptides targeting these proteins detect native structures located on the plasma membrane proteins with an affinity high enough to perform imaging/targeting. The
localization in the plasma membrane was assessed by a Systems Biology approach (I PA analysis, GO analysis, literature screening) and we perform immunohistochemistry to confirm this localization.

5. The expression level of the selected gene/protein is not substantially modified (e.g. induced) during inflammation: We have a large amount of RNA-seq and microarray data comparing control condition to conditions in which inflammation is induced (e.g. cytokine- treated or virus- or dsRNA-exposed beta cells). During inflammation pancreatic beta cells often express similar markers as those found in immune cells (T-cells, dendritic cells) infiltrating in the pancreas. It is thus of major importance to select biomarkers exclusively expressed in the beta cells and not induced during inflammation in order to quantify beta cell mass. By comparison of our RNA-seq and microarray datasets with the publicly available lllumina database we could confirm these data. This analysis was not done previously by other groups. The term "not substantially modified (e.g. induced)" means that the expression level of the candidate marker is not induced in inflammatory versus non-inflammatory conditions. This is to counter the possible effect of inflammation increasing the expression in an equal amount of decrease in beta cell-mass due to a disease condition such as diabetes, (i.e. if the decrease in beta cell mass in diabetic conditions would be about 30% and the marker as such has an increased expression of about 30% due to inflammation condition, this would not allow to detect changes in beta cell mass based on said marker).

Next, a procedure was developed to analyze the best candidate of our list at the protein level and to confirm islet- and beta cell-specificity. For the selected candidate we prepared antibodies specifically targeting the biomarker. The selected candidate and the antibodies targeting the candidate were tested in human tissue microarrays confirming their specificity for pancreas (versus surrounding tissues) and their specific expression in pancreatic islets versus exocrine tissue. The protein expression of the biomarker was subsequently validated for its specificity to beta cells versus non beta cells via immunocytochemistry on pancreatic slices of normal and diseased human and rodent pancreas.

With this set of criteria a unique biomarker was obtained selectively expressed on the plasma membrane of human and rodent pancreatic beta cells. The expression level is high enough to perform imaging/targeting and the expression level is not substantially modified by inflammation and diabetic conditions or has not been previously identified as auto-antigen. This makes it a perfect candidate for imaging/targeting of beta cells.
The great advantage of the present invention is to enable determination of pancreatic beta cell mass in diabetes mellitus (see below). Of note, there are presently no other available methods to specifically measure beta cell mass.

Similarly, said biomarker can, due to its specificity be used as a marker for detecting damaged or degraded beta cells circulating in the body of the subject. Such a circulation marker is highly sought after in the field of diabetes mellitus diagnosis, progression monitoring and treatment.

Type 1 diabetes (T1 D) is an autoimmune disease in which the body's immune system attacks and kills its own insulin-producing beta cells and kills them. A key obstacle to early detection of T1 D, to understand the evolution of the disease and to assess the effectiveness of novel therapeutic interventions to prevent or cure the disease is the lack of direct, noninvasive technologies to visualize and measure beta cell mass.

Type 2 diabetes (T2D) is a long-term metabolic disorder that is characterized by high blood sugar caused by failure of the beta cells to compensate for insulin resistance, most commonly secondary to obesity. The lack of reliable methods to determine beta cell mass also limits follow up of pancreatic islet transplantation and of patients affected by type 2 diabetes (T2D), a disease where a progressive decrease of beta cell mass (albeit of less magnitude than T1 D) is also present. To achieve the goal of beta cell imaging, there is an urgent need for beta cell specific membrane proteins which can be visualized. To solve this problem, we have selected a novel candidate beta cell biomarker by a Systems Biology approach. The results obtained indicate that:

The selected candidate is highly enriched in human pancreatic beta cells. Antibodies, Nanobodies® (Ablynx NV), small molecules or peptides directed against them (specifically binding to them) can be made into tracers to be used for PET or MRI or SPECT imaging. These tracers will bind preferentially to beta cells, enabling very good specificity and selectivity. In later stages of T1 D, when there is a severe decrease in the number of beta cells and a relative increase in alpha cells, beta cell specific biomarker will allow quantification of the remaining beta cell mass without background from non beta cells.

This biomarker will also allow follow up of pancreatic islet transplants, examination of the progressive decrease in beta cell mass in type 2 diabetic patients or of an eventual increase in beta cell mass in obese non-diabetic patients (in this case, there is an increase in beta cell mass that compensates for the insulin resistance).

The selected biomarker is not induced by inflammation and will not target infiltrating immune cells. Beta cells express autoantigens which are detected by infiltrating immune
cells. Since we compare the expression of our selected biomarker in control and inflamed beta cells and select membrane proteins which are not expressed in immune cells we will be able to follow the beta cell mass during inflammation (insulitis)

The selected candidate allow non invasive imaging of islet grafts following human islet transplantation and allow adjustment of immunosuppressive therapy to support graft survival and earlier interventions with the aim of rescuing transplants, which are under augmented immune assault.

Endogenous antibodies targeting the candidates, arising as part of the autoimmune process in T1 D, are valuable markers of autoimmunity and help in the detection of patients at a high risk to develop the disease.

The current agents used for imaging the pancreas include reagents such as glibenclamide, dopamine, fluorodeoxyglucose, fluorodithizone and DOPA. The uptake of these agents in beta cells, as compared to exocrine pancreas and non beta cells in the islets, is not sufficient to allow reliable imaging of beta-cell mass (Sweet et al, 2004).

In conclusion, the biomarker is preferentially expressed in beta cells and is expressed on the surface in sufficient amounts to enable imaging. It has extracellular domains against which a naturally occurring ligand, a peptide or and antibody (or antibody fragment) can be developed as tracer. The selected biomarker will not be modified in conditions of inflammation. These unique features will make clinical analysis of beta cell mass possible. The goal of the biomarker of the present invention is its use in the estimation and visualisation of the pancreatic beta cell mass in healthy and diseased state (diabetes or following islet transplantation). The invention will allow the development of tools for prediction and follow up of the diabetic state, for the follow up of islet transplantation, and as surrogate markers for therapeutic assays aiming to prevent diabetes and/or regenerate beta cell mass. The non-invasive imaging performed with this candidate will allow the detection of the increase of decrease in beta cell mass.

The invention therefore provides a non-invasive method for the diagnosis, prognosis, progression monitoring, or treatment monitoring of a diabetic disorder such as type 1 or type 2 diabetes mellitus (T1 D or T2D) or hyperinsulinemia, by detecting and/or measuring the beta cell mass of a subject and comparing it to a reference amount of beta cell mass of a healthy subject or of a subject with known diagnosis, prognosis, disease progression or treatment outcome. An increase of the beta cell mass in the subject under investigation points to a condition of hyperinsulinemia, while a reduction of the beta cell mass in the subject under investigation points to a condition of diabetes mellitus of type 1 or 2.
The non-invasive method for the diagnosis or prognosis of a diabetic disorder encompasses the highly specific detection and/or visualization of beta cells through the detection of beta cell-specific biomarker variant 1 of TMEM132D.

TMEM132D is a single-pass transmembrane protein, which is highly expressed in the cortical regions of the human and mouse brain. The function of the gene product is still unknown. It has been proposed that the protein may serve as a cell-surface marker for oligodendrocyte differentiation (Nomoto H. et al., (2003) J Biochem. 134: 231 ). Others reported that it may be most prominently expressed in neurons and colocalizes with actin filaments, (Walser SM. Et al., (201 1 ) Pharmacopsychiatry 44) suggesting that TMEM132D may be implicated in neuronal sprouting and connectivity in brain regions important for anxiety-related behavior. To our knowledge, no link has been made with beta cell expression.

The term "TMEM132D" as used herein hence refers to transmembrane protein 132D, encoded by the TMEM132D gene, preferably the Human TMEM132D gene, such as the gene represented by NCBI reference sequence NM_133448.2 (SEQ ID NO: 15). The amino acid sequence of the human TMEM132D protein is preferably the one represented by NCBI reference sequence Q14C87-1 (SEQ ID NO: 1 ). The expression variants referred to herein as "variant 1 of TMEM132D", "variant 2 of TMEM132D", and "variant 3 of TMEM132D" are depicted in Figure 3. Variant 2 of TMEM132D is represented by Uniprot reference Q14C87-2 (SEQ ID NO: 13), designated as "isoform 2 of TMEM132D". Variant 3 of TMEM132D is represented by Uniprot reference A0A087WUP9 (SEQ ID NO: 14).

The detection of the specific markers is done by using a radioisotopically labelled tracer molecule that binds the biomarker with high specificity. Tracers may for example be antibodies, or their fragments, single chain antibodies, nanobodies, affibodies, minibodies, diabodies, aptamers, photoaptamers, a specific ligand or interacting protein, or any small molecule or the like that has been shown to specifically bind the biomarker of choice.

The binding molecules can be known or commercially available, or can be specifically designed to detect the biomarker of the invention in a highly specific manner.

In this respect, the inventors designed binding molecules specifically binding to variant 1 of TMEM132D, e.g. by immunizing animals with the following peptide (SEQ ID NO: 1 ):

In one embodiment, the diagnostic or prognostic method of the invention uses Positron Emission Tomography (PET), a nuclear medicine medical imaging technique which produces a three-dimensional image or map of functional processes in the body. The system detects pairs of gamma rays emitted indirectly by a positron-emitting radioisotope, which is introduced into the body through a tracer molecule e.g. a specific biomarker binding molecule. Images of the radioisotope labeled tracer in the body are then reconstructed by computer analysis. In modern scanners, a PET scan is combined with a CT X-ray scan (PET-CT) performed on the patient at the same time, in the same machine, providing the structural reference of the organs etc.

In an alternative embodiment, single photon emission computed tomography (SPECT) imaging can be used in the diagnostic or prognostic method of the invention. SPECT uses a gamma camera to acquire multiple 2-D projections from multiple angles. A computer is then used to apply a tomographic reconstruction algorithm to the multiple projections, yielding a 3-D dataset. This dataset may then be manipulated to show thin slices along any chosen axis of the body.

Preferred labels used in PET or PET-CT are short-lived radioisotopes such as carbon-1 1 (-20 min), nitrogen-13 (-10 min), oxygen-15 (-2 min), galium-68 (-68 minutes) and fluorine-18 (-1 10 min) or medium-lived radioisotopes such as zirconium-89 (-4 days) and
iodine-124 (-4 days) when appropriate. Several novel tracer molecules have been developed including modified Exendin derivatives (Poly-Chelator Exendin, cleavable linkers and click-chemistry for easy 18F labelling), a PAC1 receptor targeting peptide, GIP derivatives for targeting the GIP receptor, a peptide targeting GPR54, and nanoparticles for MRI and optical imaging coupled with Exendin-4 and glibenclamide. GMP kits for clinical imaging for 111ln and 68Ga labelling of Exendin have been developed, fully GMP certified, and can be distributed in Europe after approval of a certified person.

These novel tracers have been evaluated in vitro and in vivo. Poly-chelator-Exendin has identical pharmacokinetic properties when compared to the lead compound of the project but can be labelled with much higher specific activities, enabling improved small animal imaging with higher activity doses and injection of lower amounts of peptide (also for human use). Other tracers (GIP, PAC1 targeting peptide, GPR54 targeting peptide) do not appear to be suitable for in vivo imaging of pancreatic beta cells although in tumour imaging, PAC1 targeting peptide shows favourable results. Non-invasive islet imaging is also being developed with high field MRI and the use of nanoparticles and probes targeting beta cells via the lead compound as well as manganese contrast enhancement. xf-FDOCT has been further established as a new and powerful method to follow islets and diabetes progression in autoimmune diabetic mouse (NOD) models, to visualize blood flow in pancreatic islets and to dynamically monitor tracer distribution within the pancreas of live mice.

Preparation and assessment of the GMP clinical grade SPECT and PET tracer targeting GLP-1 R is completed. Protocols for quantitative SPECT imaging have been implemented and optimized, as well as dosimetry protocols. Full documentation according to EMA standards for the Exendin based tracers has been achieved for clinical studies and the respective documents allow easy modification for use with other Exendin-based tracers (except for the production IMPD that needs to be prepared for every tracer molecule based on the labelling protocol). As already mentioned, the kits together with full documentation can now be distributed throughout Europe for multicenter studies after approval by a qualified person. Clinical trials with Exendin are under way..

A typical in vivo diagnostic method encompassed by the invention is as follows: a) introducing an isotopically labelled tracer molecule, specifically binding to the beta cell specific biomarker into a subject,

b) the in vivo visualisation of a tracer molecule specifically binding to the beta cells in the pancreas using PET, PET-CT or SPECT,
c) quantification of the beta cells mass in said subject, d) comparison of the beta cell mass data obtained in step c) with the beta cell mass of a healthy subject, and

e) diagnosing the subject as having diabetes or being at risk of having diabetes when the level of beta cell mass obtained in step c) is reduced as compared to that of a healthy subject and diagnosing the subject as having hyperinsulinemia or being at risk of having hyperinsulinemia when the level of beta cell mass obtained in step c) is increased as compared to that of a healthy subject.

The method of in vivo diagnosis or prognosis can be used to diagnose insulin-related disorders such as typel or type 2 diabetes mellitus, hyperinsulinemia and pancreatic cancer such as the occurrence of neuroendocrine tumors of the pancreas like insulinoma derived from the beta cells.

For treating insulin-related disorders, pancreatic islet transplantation is an option. Typically, the Edmonton protocol is applied wherein specialized enzymes are used to remove islets from the pancreas of a deceased donor. Because the islets are fragile, transplantation occurs soon after they are removed. Typically a patient receives at least 10,000 islet "equivalents" per kilogram of body weight, extracted from two or more donor pancreases. Patients often require two transplants to achieve insulin independence. Some transplants have used fewer islet equivalents taken from a single donated pancreas. Transplants are often performed by a radiologist, who uses x rays and ultrasound to guide placement of a catheter through the upper abdomen and into the portal vein of the liver. The islets are then infused slowly through the catheter into the liver. The patient receives a local anesthetic and a sedative. In some cases, a surgeon may perform the transplant through a small incision, using general anesthesia.

The key of success for such a beta cell transplantation treatment is of course the purity of the beta cell preparation used for the transplantation. The invention provides for methods of specifically isolating beta cells for use in islet transplantation and tools for follow up of transplanted beta cells.

In a further embodiment, the invention provides for methods to isolate and/or purify pancreatic beta cells from pancreatic tissue, by visualizing or labeling the beta cells in a specific manner using TMEM132D, preferably variant 1 thereof.

Alternatively, the method provides a method for identification of stem cell populations in order to derive functional insulin-expressing cells comprising the following steps:
a) tagging the treated stem cells with a labelled binding molecule specifically binding to TMEM132D, preferably variant 1 thereof,

The method of the invention can in certain embodiments further comprise the steps of: c) performing immunohistochemistry to identify the number of beta stem cells, and to define the new beta cell mass and

d) follow up of therapeutic strategies and detect newly formed beta cell mass.

The above separation methods can for example be performed by separating labelled cells from non-labelled cells using standard separation techniques based on the retention of labelled binding molecules directed to the biomarker of the present invention.

One option is to use antibodies, nanobodies, aptamers, oligonucleotides or other specific binding agents or ligands, specifically binding to the biomarker of the invention, for tagging cells of interest with a small magnetic particle or magnetic bead. The bead-binding molecule conjugate is then directed to the beta-cells in the pancreatic cell preparation and the beta cells can be specifically purified from the total pancreatic cell preparation by using e.g. an electromagnetic field. In some systems, the sample is processed through a column that generates a magnetic field when placed within the separator instrument, retaining only the labelled cells.

Other systems offer simplified versions of the magnetic separator. Instead of a column and separator instrument, these systems use a simple magnet to directly retain the labeled cells within the tube, while the supernatant is drawn off. Some of these systems can be used in a positive or negative selection manner. Negative or enrichment selection means that unwanted cells can be labeled (captured), leaving the cells of interest label- free. The magnetic particles do not interfere with flow cytometry, nor do they interfere with cell growth, according to Hammonds, so cells that have been isolated using such a system can be further cultured.

Magnetic separation has proven uniquely powerful and broadly applicable, sometimes leading to 70% recovery of the target cells and up to 98% purity while retaining cell viability.

Alternatively, an efficient non-magnetic separation method, based on work on tetrameric antibody complexes (TACs) works by linking unwanted cells in a sample together, forming clumps. After labelling, the sample is layered over a buoyant density medium such as
Ficoll. The labelled cells pellet with when centrifuged, while the desired, unlabelled cells are recovered at the interface. This method is fast and the cells obtained are not labelled with antibodies and are untouched.

Many of these techniques are most powerful in combination. The skilled person would however be aware of other methods to selectively purify specific cell-types.

The term "binding molecules" used in the methods and kits of the invention refers to all suitable binding molecules that are specifically binding or interacting with the biomarker of the invention and that can be used in the methods and kits of the present invention. Examples of suitable binding agents are antibodies, monoclonal- or polyclonal antibodies, nanobodies, affibodies, diabodies, minibodies, single chain antibodies, antibody fragments, aptamers, photoaptamers, oligonucleotides, lipocalins, specifically interacting small molecules, Molecular Imprinting Polymers (MIPs), DARPins, ankyrins, specifically interacting proteins, peptidomimetics, biomimetics or peptides, and other molecules that specifically bind to the biomarker.

As used herein, the term 'antibody' refers to polyclonal antibodies, monoclonal antibodies, humanized antibodies, single-chain antibodies, and fragments thereof such as Fab, F(ab)2, Fv, and other fragments that retain the antigen binding function of the parent antibody. As such, an antibody may refer to an immunoglobulin or glycoprotein, or fragment or portion thereof, or to a construct comprising an antigen-binding portion comprised within a modified immunoglobulin-like framework, or to an antigen-binding portion comprised within a construct comprising a non- immunoglobulin-like framework or scaffold.

As used herein, the term 'monoclonal antibody' refers to an antibody composition having a homogeneous antibody population. The term is not limited regarding the species or source of the antibody, nor is it intended to be limited by the manner in which it is made. The term encompasses whole immunoglobulins as well as fragments and others that retain the antigen binding function of the antibody. Monoclonal antibodies of any mammalian species can be used in this invention. In practice, however, the antibodies will typically be of rat or murine origin because of the availability of rat or murine cell lines for use in making the required hybrid cell lines or hybridomas to produce monoclonal antibodies.

As used herein, the term 'polyclonal antibody' refers to an antibody composition having a heterogeneous antibody population. Polyclonal antibodies are often derived from the pooled serum from immunized animals or from selected humans.
'Heavy chain variable domain of an antibody or a functional fragment thereof, as used herein, means (i) the variable domain of the heavy chain of a heavy chain antibody, which is naturally devoid of light chains (also indicated hereafter as VHH), including but not limited to the variable domain of the heavy chain of heavy chain antibodies of camelids or sharks or (ii) the variable domain of the heavy chain of a conventional four-chain antibody (also indicated hereafter as VH), including but not limited to a camelized (as further defined herein) variable domain of the heavy chain of a conventional four-chain antibody (also indicated hereafter as camelized VH) or any functional fragments thereof, such as but not limited to one or more stretches of amino acid residues (i.e. small peptides) that are particularly suited for binding to a tumor antigen and which are present in, and/or may be incorporated into, the VHH'S as disclosed herein (or may be based on and/or derived from CDR sequences of the VHH'S as disclosed herein).

As further described hereinbelow, the amino acid sequence and structure of a heavy chain variable domain of an antibody can be considered, without however being limited thereto, to be comprised of four framework regions or 'FR's', which are referred to in the art and hereinbelow as 'framework region 1 ' or 'FR1 '; as 'framework region 2' or 'FR2'; as 'framework region 3' or 'FR3'; and as 'framework region 4' or 'FR4', respectively, which framework regions are interrupted by three complementary determining regions or 'CDR's', which are referred to in the art as 'complementarity determining region 1 ' or 'CDR1 '; as 'complementarity determining region 2' or 'CDR2'; and as 'complementarity determining region 3' or 'CDR3', respectively.

An amino acid sequence, in particular an antibody fragment, such as a VHH or functional fragments thereof, as disclosed herein is considered to be '(in) essentially isolated (form)' as used herein, when it has been extracted or purified from the host cell and/or medium in which it is produced.

In respect of the amino acid sequences, in particular an antibody fragment, such as a VH or functional fragments thereof H, as disclosed herein, the terms 'binding region', 'binding site' or 'interaction site' present on the amino acid sequences as disclosed herein shall herein have the meaning of a particular site, region, locus, part, or domain present on the target molecule, which particular site, region, locus, part, or domain is responsible for binding to that target molecule. Such binding region thus essentially consists of that particular site, region, locus, part, or domain of the target molecule, which is in contact with the amino acid sequence when bound to that target molecule.

As used herein, the terms 'complementarity determining region' or 'CDR' within the context of antibodies refer to variable regions of either the H (heavy) or the L (light) chains
(also abbreviated as VH and VL, respectively) and contain the amino acid sequences capable of specifically binding to antigenic targets. These CDR regions account for the basic specificity of the antibody for a particular antigenic determinant structure. Such regions are also referred to as "hypervariable regions." The CDRs represent non- contiguous stretches of amino acids within the variable regions but, regardless of species, the positional locations of these critical amino acid sequences within the variable heavy and light chain regions have been found to have similar locations within the amino acid sequences of the variable chains. The variable heavy and light chains of all canonical antibodies each have 3 CDR regions, each non- contiguous with the others (termed L1 , L2, L3, H1 , H2, H3) for the respective light (L) and heavy (H) chains.

As also further described hereinbelow, the total number of amino acid residues in a heavy chain variable domain of an antibody (including a VHH or a VH) can be in the region of 1 10- 130, is preferably 1 12-1 15, and is most preferably 1 13. It should however be noted that parts, fragments or analogs of a heavy chain variable domain of an antibody are not particularly limited as to their length and/or size, as long as such parts, fragments or analogs retain (at least part of) the functional activity, and/or retain (at least part of) the binding specificity of the original a heavy chain variable domain of an antibody from which these parts, fragments or analogs are derived from. Parts, fragments or analogs retaining (at least part of) the functional activity, and/or retaining (at least part of) the binding specificity of the original heavy chain variable domain of an antibody from which these parts, fragments or analogs are derived from are also further referred to herein as 'functional fragments' of a heavy chain variable domain.

The amino acid residues of a variable domain of a heavy chain variable domain of an antibody (including a VHH or a VH) are numbered according to the IMGT numbering (international ImMunoGeneTics information system).

Hence, in the present description, aspects, claims and figures, the numbering according to IMGTas applied to VHH domains will be followed, unless indicated otherwise.

Generally, it should be noted that the term 'heavy chain variable domain' as used herein in its broadest sense is not limited to a specific biological source or to a specific method of preparation. For example, as will be discussed in more detail below, the heavy chain variable domains derived from heavy chain antibodies (i.e. VHH'S) as disclosed herein can be obtained (1 ) by isolating the VHH domain of a naturally occurring heavy chain antibody;

(2) by expression of a nucleotide sequence encoding a naturally occurring VHH domain; (3)
by 'camelization' (as described below) of a naturally occurring VH domain from any animal species, in particular a species of mammal, such as from a human being, or by expression of a nucleic acid encoding such a camelized VH domain; (4) by 'camelisation' of a 'domain antibody' or 'Dab' as described by Ward et al (supra), or by expression of a nucleic acid encoding such a camelized VH domain (5) using synthetic or semi-synthetic techniques for preparing proteins, polypeptides or other amino acid sequences; (6) by preparing a nucleic acid encoding a VHH using techniques for nucleic acid synthesis, followed by expression of the nucleic acid thus obtained; and/or (7) by any combination of the foregoing. Suitable methods and techniques for performing the foregoing will be clear to the skilled person based on the disclosure herein and for example include the methods and techniques described in more detail hereinbelow.

The term 'affinity', as used herein, refers to the degree to which a polypeptide, in particular an immunoglobulin, such as an antibody, or an immunoglobulin fragment, such as a VHH, binds to an antigen so as to shift the equilibrium of antigen and polypeptide toward the presence of a complex formed by their binding. Thus, for example, where an antigen and antibody (fragment) are combined in relatively equal concentration, an antibody (fragment) of high affinity will bind to the available antigen so as to shift the equilibrium toward high concentration of the resulting complex. The dissociation constant is commonly used to describe the affinity between the protein binding domain and the antigenic target. Typically, the dissociation constant is lower than 10"5 M. Preferably, the dissociation constant is lower than 1 0"6 M, more preferably, lower than 10"7 M. Most preferably, the dissociation constant is lower than 10"8 M, such as lower than 10"9 M.

The terms 'specifically bind' and 'specific binding', as used herein, generally refers to the ability of a polypeptide, in particular an immunoglobulin, such as an antibody, or an immunoglobulin fragment, such as a VHH or functional fragments thereof, to preferentially bind to a particular antigen that is present in a homogeneous mixture of different antigens. In certain embodiments, a specific binding interaction will discriminate between desirable and undesirable antigens in a sample, in some embodiments more than about 1 0 to 100- fold or more (e.g., more than about 1000- or 1 0,000-fold).

Accordingly, an amino acid sequence, in particular an antibody fragment, such as a VHH or functional fragments thereof, as disclosed herein is said to 'specifically bind to' a particular target when that amino acid sequence has affinity for, specificity for and/or is specifically binding to that target (or for at least one part or fragment thereof).

An amino acid sequence, in particular an antibody fragment, such as a VHH or functional fragments thereof as disclosed herein is said to be 'specific for a first target antigen of
interest as opposed to a second target antigen of interest' when it binds to the first target antigen of interest with an affinity that is at least 5 times, such as at least 10 times, such as at least 100 times, and preferably at least 1000 times higher than the affinity with which that amino acid sequence as disclosed herein binds to the second target antigen of interest. Accordingly, in certain embodiments, when an amino acid sequence as disclosed herein is said to be 'specific for' a first target antigen of interest as opposed to a second target antigen of interest, it may specifically bind to (as defined herein) the first target antigen of interest, but not to the second target antigen of interest.

The 'specificity' of an amino acid sequence, in particular an antibody fragment, such as a VHH, or functional fragments thereof as disclosed herein can be determined based on affinity and/or avidity. The 'affinity' of an amino acid sequence as disclosed herein is represented by the equilibrium constant for the dissociation of the amino acid sequence as disclosed herein and the target protein of interest to which it binds. The lower the KD value, the stronger the binding strength between the amino acid sequence as disclosed herein and the target protein of interest to which it binds. Alternatively, the affinity can also be expressed in terms of the affinity constant (KA), which corresponds to 1 /KD. The binding affinity of an amino acid sequence as disclosed herein can be determined in a manner known to the skilled person, depending on the specific target protein of interest.

The 'avidity' of an amino acid sequence as disclosed herein is the measure of the strength of binding between the amino acid sequence as disclosed herein and the pertinent target protein of interest. Avidity is related to both the affinity between a binding site on the target protein of interest and a binding site on the amino acid sequence as disclosed herein and the number of pertinent binding sites present on the amino acid sequence as disclosed herein. Typically, the amino acid sequences as disclosed herein will bind to a target protein of interest with a dissociation constant (KD) of less than about 1 micromolar (1 μΜ), and preferably less than about 1 nanomolar (1 nM) [i.e., with an association constant (KA) of about 1 ,000,000 per molar (106 M"1 , 1 E6 M) or more and preferably about 1 ,000,000,000 per molar (109 M"1 , 1 E9 /M) or more]. A KD value greater than about 1 millimolar is generally considered to indicate non-binding or non-specific binding. It is generally known in the art that the KD can also be expressed as the ratio of the dissociation rate constant of a complex, denoted as kOff (expressed in seconds"1 or s"1), to the rate constant of its association, denoted kOn (expressed in molar"1 seconds"1 or M"1 s"1). In particular, an amino acid sequence as disclosed herein will bind to the target protein of interest with a kOff ranging between 0.1 and 0.0001 s"1 and/or a kOn ranging between 1 ,000 and 1 ,000,000 M"1 s"1. Binding affinities, kOff and kOn rates may be determined by
means of methods known to the person skilled in the art, for example ELISA methods, isothermal titration calorimetry, surface plasmon resonance, fluorescence-activated cell sorting analysis, and the more.

An amino acid sequence, in particular an antibody fragment, such as a VHH, as disclosed herein is considered to be '(in) essentially isolated (form)' as used herein, when it has been extracted or purified from the host cell and/or medium in which it is produced.

In respect of the amino acid sequences, in particular antibody fragments, such as a VHH'S or functional fragments thereof, as disclosed herein, the terms 'binding region', 'binding site' or 'interaction site' present on the amino acid sequences as disclosed herein shall herein have the meaning of a particular site, part, domain or stretch of amino acid residues present on the amino acid sequence as disclosed herein that is responsible for binding to a target molecule. Such binding region essentially consists of specific amino acid residues from the amino acid sequence as disclosed herein which are in contact with the target molecule.

The 'half-life' of an amino acid sequence, in particular an antibody fragment, such as a VHH or functional fragments thereof, as disclosed herein can generally be defined as the time that is needed for the in vivo serum concentration of the amino acid sequence as disclosed herein to be reduced by 50%. The in vivo half-life of an amino acid sequence as disclosed herein can be determined in any manner known to the person skilled in the art, such as by pharmacokinetic analysis. As will be clear to the skilled person, the half-life can be expressed using parameters such as the t1/2-alpha, t1/2-beta and the area under the curve (AUC). An increased half-life in vivo is generally characterized by an increase in one or more and preferably in all three of the parameters t1/2-alpha, t1/2-beta and the area under the curve (AUC).

Aptamers that bind specifically to the biomarker of the invention can be obtained using the so called SELEX or Systematic Evolution of Ligands by Exponential enrichment. In this system, multiple rounds of selection and amplification can be used to select for DNA or RNA molecules with high specificity for a target of choice, developed by Larry Gold and coworkers and described in US patent 6,329,145. Recently a more refined method of designing co-called photoaptamers with even higher specificity has been described in US patent 6,458,539 by the group of Larry Gold.

Methods of identifying binding agents such as interacting proteins and small molecules are also known in the art. Examples are two-hybrid analysis, immunoprecipitation methods and the like.
In addition, the invention also provides tools and methods for the identification of binding molecules, such as peptides or small molecules, monoclonal- or polyclonal antibodies, nanobodies, affibodies, minibodies, diabodies, single chain antibodies, antibody fragments, aptamers, photoaptamers, lipocalins, specifically interacting small molecules, Molecular Imprinting Polymers (MIPs), DARPins, ankyrins, specifically interacting proteins or peptides, and other molecules that specifically bind to the biomarker, e.g. using cells or cell-lines that do or do not express TMEM132D, preferably variant 1 thereof.

To this end, the invention provides several cells and/or cell-lines (rodent pancreatic islets, rat INS-1 E, cells and the human beta cell line EndoC-BH1 ) that are TMEM132D variant 1 positive and two cell-lines (human PANC-1 and CAPAN-2 cells) that are TMEM132D variant 1 negative. These cells or cell-lines can be used to screen for binding agents or compounds that specifically bind to cells positive for variant 1 of TMEM132D, but not to cells negative for variant 1 of TMEM132D in order to identify new tracer molecules for visualization of beta-cells e.g. in PET, PET-CT or SPECT analysis, or in immunochemical or immunofluorescent detection analysis.

The invention further provides methods for preparing or generating VHH domain sequences or functional fragments thereof specifically binding to variant 1 of TMEM132D, as well as methods for producing nucleic acids encoding these and host cells, products and compositions comprising these heavy chain variable domain sequences. Some preferred but non-limiting examples of such methods will become clear from the further description herein.

As will be clear to the skilled person, one particularly useful method for preparing heavy chain variable domain sequences as disclosed herein generally comprises the steps of:

In particular embodiments envisaged herein, the heavy chain variable domain sequences specifically binding to variant 1 of TMEM132D can be obtained by methods which involve generating a random library of VHH sequences and screening this library for an VHH sequence capable of specifically binding to variant 1 of TMEM132D.

Accordingly, in particular embodiments, methods for preparing a heavy chain variable domain sequence as disclosed herein comprise the steps of
a) providing a set, collection or library of amino acid sequences of VHH domains; and b) screening said set, collection or library of VHH domains for amino acid sequences that can bind to and/or have affinity for variant 1 of TM EM 1 32D .

and

c) isolating the VHH domains that can bind to and/or have affinity for variant 1 of TME M 1 32D.

In such a method, the set, collection or library of VHH sequences may be any suitable set, collection or library of amino acid sequences. For example, the set, collection or library of VHHS sequences may be a set, collection or library of immunoglobulin fragment sequences (as described herein), such as a naive set, collection or library of immunoglobulin fragment sequences; a synthetic or semi-synthetic set, collection or library of immunoglobulin fragment sequences; and/or a set, collection or library of immunoglobulin fragment sequences that have been subjected to affinity maturation.

In particular embodiments of this method, the set, collection or library of VHH sequences may be an immune set, collection or library of immunoglobulin fragment sequences, for example derived from a mammal that has been suitably immunized with variant 1 of TME M 1 32D or with a suitable antigenic determinant based thereon or derived therefrom, such as an antigenic part, fragment, region, domain, loop or other epitope thereof. In one particular aspect, said antigenic determinant may be an extracellular part, region, domain, loop or other extracellular epitope(s).

In the above methods, the set, collection or library of VHH sequences may be displayed on a phage, phagemid, ribosome or suitable micro-organism (such as yeast), such as to facilitate screening. Suitable methods, techniques and host organisms for displaying and screening (a set, collection or library of) amino acid sequences will be clear to the person skilled in the art, for example on the basis of the further disclosure herein. Reference is also made to the review by Hoogenboom in Nature Biotechnology, 23, 9, 1 1 05-1 1 16 (2005).

In other embodiments, the methods for generating the heavy chain variable domain sequences as disclosed herein comprises at least the steps of:

b) screening said collection or sample of cells for cells that express a VHH amino acid sequence that can bind to and/or have affinity for variant 1 of TM EM 1 32D;
and

c) either (i) isolating said amino acid sequence; or (ii) isolating from said cell a nucleic acid sequence that encodes said amino acid sequence, followed by expressing said amino acid sequence.

The collection or sample of cells may for example be a collection or sample of B-cells. Also, in this method, the sample of cells may be derived from a mammal that has been suitably immunized with variant 1 of TMEM132D or with a suitable antigenic determinant based thereon or derived therefrom, such as an antigenic part, fragment, region, domain, loop or other epitope thereof. In one particular embodiment, the antigenic determinant may be an extracellular part, region, domain, loop or other extracellular epitope(s).

In other embodiments, the method for generating a heavy chain variable domain sequence specifically binding to variant 1 of TMEM132D, may comprise at least the steps of:

b) screening said set, collection or library of nucleic acid sequences for nucleic acid sequences that encode a VHH amino acid sequence that can bind to and/or has affinity for variant 1 of TMEM132D;

and

c) isolating said nucleic acid sequence, followed by expressing said amino acid sequence.

In the above methods, the set, collection or library of nucleic acid sequences encoding amino acid sequences may for example be a set, collection or library of nucleic acid sequences encoding a naive set, collection or library of immunoglobulin fragment sequences; a set, collection or library of nucleic acid sequences encoding a synthetic or semi-synthetic set, collection or library of immunoglobulin fragment sequences; and/or a set, collection or library of nucleic acid sequences encoding a set, collection or library of immunoglobulin fragment sequences that have been subjected to affinity maturation.

In particular, in such a method, the set, collection or library of nucleic acid sequences encodes a set, collection or library of VHH domains specifically binding to variant 1 of TMEM132D.

In the above methods, the set, collection or library of nucleotide sequences may be displayed on a phage, phagemid, ribosome or suitable micro-organism (such as yeast),
such as to facilitate screening. Suitable methods, techniques and host organisms for displaying and screening (a set, collection or library of) nucleotide sequences encoding amino acid sequences will be clear to the person skilled in the art, for example on the basis of the further disclosure herein. Reference is also made to the review by Hoogenboom in Nature Biotechnology, 23, 9, 1 105-1 1 16 (2005).

The invention also relates to VHH sequences that are obtainable or obtained by the above methods, or alternatively by a method that comprises one of the above methods and in addition at least the steps of determining the nucleotide sequence or amino acid sequence of said VHH sequence; and of expressing or synthesizing said VHH sequence in a manner known per se, such as by expression in a suitable host cell or host organism or by chemical synthesis.

In some cases, the methods for producing the VHH amino acid sequences binding specifically to variant 1 of TMEM132D as envisaged herein may further comprise the step of isolating from the amino acid sequence library at least one VHH domain having detectable binding affinity for, or detectable in vitro effect on variant 1 of TMEM132.

These methods may further comprise the step of amplifying a sequence encoding at least one VHH domain having detectable binding affinity for, or detectable in vitro effect on the activity of variant 1 of TMEM132D. For example, a phage clone displaying a particular amino acid sequence, obtained from a selection step of a method described herein, may be amplified by reinfection of a host bacteria and incubation in a growth medium.

In particular embodiments, these methods may encompass determining the sequence of the one or more amino acid sequences capable of binding to variant 1 of TMEM132D.

Where a heavy chain variable domain sequence, comprised in a set, collection or library of amino acid sequences, is displayed on a suitable cell or phage or particle, it is possible to isolate from said cell or phage or particle, the nucleotide sequence that encodes that amino acid sequence. In this way, the nucleotide sequence of the selected amino acid sequence library member(s) can be determined by a routine sequencing method.

In further particular embodiments, the methods for producing a VHH domain as envisaged herein comprise the step of expressing said nucleotide sequence(s) in a host organism under suitable conditions, so as to obtain the actual desired amino acid sequence. This step can be performed by methods known to the person skilled in the art.

In addition, the obtained VHH domain sequences having detectable binding affinity for, or detectable in vitro effect on the activity of variant 1 of TMEM132D, may be synthesized as soluble protein construct, optionally after their sequence has been identified.
For instance, the VHH domain sequences obtained, obtainable or selected by the above methods can be synthesized using recombinant or chemical synthesis methods known in the art. Also, the amino acid sequences obtained, obtainable or selected by the above methods can be produced by genetic engineering techniques. Thus, methods for synthesizing the VHH sequences obtained, obtainable or selected by the above methods may comprise transforming or infecting a host cell with a nucleic acid or a vector encoding an amino acid sequence having detectable binding affinity for, or detectable in vitro effect on the activity of variant 1 of TMEM132D. Accordingly, the VHH sequences having detectable binding affinity for, or detectable in vitro effect on the activity of variant 1 of TMEM132D can be made by recombinant DNA methods. DNA encoding the amino acid sequences can be readily synthesized using conventional procedures. Once prepared, the DNA can be introduced into expression vectors, which can then be transformed or transfected into host cells such as E. coli or any suitable expression system, in order to obtain the expression of amino acid sequences in the recombinant host cells and/or in the medium in which these recombinant host cells reside.

It should be understood, as known by someone skilled in the art of protein expression and purification, that the VHH domain produced from an expression vector using a suitable expression system may be tagged (typically at the N-terminal or C-terminal end of the amino acid sequence) with e.g. a His-tag or other sequence tag for easy purification.

Transformation or transfection of nucleic acids or vectors into host cells may be accomplished by a variety of means known to the person skilled in the art including calcium phosphate-DNA co-precipitation, DEAE-dextran-mediated transfection, polybrene- mediated transfection, electroporation, microinjection, liposome fusion, lipofection, protoplast fusion, retroviral infection, and biolistics.

Suitable host cells for the expression of the desired heavy chain variable domain sequences may be any eukaryotic or prokaryotic cell (e.g., bacterial cells such as E. coli, yeast cells, mammalian cells, avian cells, amphibian cells, plant cells, fish cells, and insect cells), whether located in vitro or in vivo. For example, host cells may be located in a transgenic plant.

Thus, the application also provides methods for the production of VHH domain sequences having detectable binding affinity for, or detectable in vitro effect on the activity of variant 1 of TMEM132D comprising transforming, transfecting or infecting a host cell with nucleic acid sequences or vectors encoding such VHH sequences and expressing their amino acid sequences under suitable conditions.
In yet another embodiment, the invention further provides methods for the manufacture ('or the production of which is equivalent wording) a pharmaceutical composition as disclosed herein.

In particular embodiments, the invention provides methods for producing a pharmaceutical composition as disclosed herein, at least comprising the steps of:

- obtaining at least one VHH or a functional fragment thereof, which specifically binds to variant 1 of TMEM132D, and

- formulating said VHH or functional fragment thereof in a pharmaceutical composition.

In particular embodiments of these methods, the step of obtaining at least one heavy chain variable domain or functional fragment thereof, which specifically binds to variant 1 of TMEM132D comprises:

(a) expressing a nucleotide sequence encoding a VHH or functional fragment thereof, which specifically binds to variant 1 of TMEM132D, and optionally

b) screening said set, collection or library of VHH domain sequences or sequences of functional fragments thereof for sequences that specifically bind to and/or have affinity for variant 1 of TMEM132D, and

c) optionally isolating the VHH sequences or sequences of functional fragments thereof that specifically bind to and/or have affinity for variant 1 of TMEM132D.

In certain aspects, the VHH domains or functional fragments thereof specifically binding to variant 1 of TMEM132D as disclosed herein may be optionally linked to one or more further groups, moieties, or residues via one or more linkers. These one or more further groups, moieties or residues can serve for binding to other targets of interest. It should be clear that such further groups, residues, moieties and/or binding sites may or may not provide further functionality to the heavy chain variable domains as disclosed herein and may or may not modify the properties of the heavy chain variable domain as disclosed herein. Such groups, residues, moieties or binding units may also for example be chemical groups which can be biologically active.
These groups, moieties or residues are, in particular embodiments, linked N- or C- terminally to the heavy chain variable domain, in particularly C-terminally linked.

In particular embodiments, the VHH domains or functional fragments thereof specifically binding to variant 1 of TMEM132D as disclosed herein may also have been chemically modified. For example, such a modification may involve the introduction or linkage of one or more functional groups, residues or moieties into or onto the heavy chain variable domain.

These groups, residues or moieties may confer one or more desired properties or functionalities to the heavy chain variable domain. Examples of such functional groups will be clear to the skilled person.

For example, the introduction or linkage of such functional groups to a heavy chain variable domain can result in an increase in the solubility and/or the stability of the heavy chain variable domain, in a reduction of the toxicity of the heavy chain variable domain, or in the elimination or attenuation of any undesirable side effects of the heavy chain variable domain, and/or in other advantageous properties.

In particular embodiments, the one or more groups, residues, moieties are linked to the heavy chain variable domain via one or more suitable linkers or spacers.

While the VHH domains specifically binding to variant 1 of TMEM132D as disclosed herein are preferably in monomeric form (as further described herein), in particular alternative embodiments, two or more of the VHH domains or functional fragments thereof, specifically binding to variant 1 of TMEM132D as disclosed herein may be linked to each other or may be interconnected. In particular embodiments, the two or more heavy chain variable domains or functional fragments thereof are linked to each other via one or more suitable linkers or spacers. Suitable spacers or linkers for use in the coupling of different heavy chain variable domains as disclosed herein will be clear to the skilled person and may generally be any linker or spacer used in the art to link peptides and/or proteins.

Some particularly suitable linkers or spacers include for example, but are not limited to, polypeptide linkers such as glycine linkers, serine linkers, mixed glycine/serine linkers, glycine- and serine-rich linkers or linkers composed of largely polar polypeptide fragments, or homo- or heterobifunctional chemical crosslinking compounds such as glutaraldehyde or, optionally PEG-spaced, maleimides or NHS esters.

For example, a polypeptide linker or spacer may be a suitable amino acid sequence having a length between 1 and 50 amino acids, such as between 1 and 30, and in particular between 1 and 10 amino acid residues. It should be clear that the length, the
degree of flexibility and/or other properties of the linker(s) may have some influence on the properties of the heavy chain variable domains, including but not limited to the affinity, specificity or avidity for the fungal target. It should be clear that when two or more linkers are used, these linkers may be the same or different. In the context and disclosure of the present invention, the person skilled in the art will be able to determine the optimal linkers for the purpose of coupling heavy chain variable domains as disclosed herein without any undue experimental burden.

The present invention also encompasses parts, fragments, analogs, mutants, variants, and/or derivatives of the radiolabeled VHH domains specifically binding to variant 1 of TMEM132D as disclosed herein and/or polypeptides comprising or essentially consisting of one or more of such parts, fragments, analogs, mutants, variants, and/or derivatives, as long as these parts, fragments, analogs, mutants, variants, and/or derivatives are suitable for the purposes envisaged herein.

Such parts, fragments, analogs, mutants, variants, and/or derivatives according to the invention are still capable of specifically binding to variant 1 of TMEM132D.

For example, the invention provides a number of stretches of amino acid residues (i.e. small peptides), also referred to herein as CDR sequences of the VHH'S as disclosed herein, that are particularly suited for binding to variant 1 of TMEM132D. These stretches may be regarded as being functional fragments of the VHH'S as disclosed herein and may be present in, and/or may be incorporated into any suitable scaffold (protein), such as but not limited to the VHH'S as disclosed herein, in particular in such a way that they form (part of) the antigen binding site of that suitable scaffold or VHH- It should however be noted that the invention in its broadest sense is not limited to a specific structural role or function that these stretches of amino acid residues may have in the scaffolds or VHH'S as disclosed herein, as long as these stretches of amino acid residues allow these scaffolds or VHH'S as disclosed herein to specifically bind to variant 1 of TMEM132D.

In a further aspect, the present invention provides nucleic acid sequences encoding the VHH domain amino acid sequences in the compositions as disclosed herein (or suitable fragments thereof). These nucleic acid sequences can also be in the form of a vector or a genetic construct or polynucleotide. The nucleic acid sequences as disclosed herein may be synthetic or semi-synthetic sequences, nucleotide sequences that have been isolated from a library (and in particular, an expression library), nucleotide sequences that have been prepared by PCR using overlapping primers, or nucleotide sequences that have been prepared using techniques for DNA synthesis known per se.
The genetic constructs as disclosed herein may be DNA or RNA, and are preferably double-stranded DNA. The genetic constructs of the invention may also be in a form suitable for transformation of the intended host cell or host organism in a form suitable for integration into the genomic DNA of the intended host cell or in a form suitable for independent replication, maintenance and/or inheritance in the intended host organism. For instance, the genetic constructs of the invention may be in the form of a vector, such as for example a plasmid, cosmid, YAC, a viral vector or transposon. In particular, the vector may be an expression vector, i.e., a vector that can provide for expression in vitro and/or in vivo (e.g. in a suitable host cell, host organism and/or expression system).

Accordingly, in another further aspect, the present invention also provides vectors comprising one or more nucleic acid sequences as disclosed herein.

In still a further aspect, the present invention provides hosts or host cells that express or are capable of expressing one or more amino acid sequences as disclosed herein. Suitable examples of hosts or host cells for expression of the VHH sequences, polypeptides of the invention will be clear to the skilled person.

In a further aspect, the present invention provides polypeptides (also referred to herein as "polypeptides as disclosed herein") that comprise or essentially consist of at least one VHH sequence of the present invention that specifically binds to variant 1 of TMEM132D. The polypeptides of the invention may comprise at least one VHH or functional fragments thereof as disclosed herein and optionally one or more further groups, moieties, residues optionally linked via one or more linkers.

In particularly preferred embodiments, the present invention provides polypeptides and pharmaceutical compositions comprising a VHH domain in its monomeric form, i.e. comprising only one VHH domain so as to minimize the in vivo half-life of said polypeptides and pharmaceutical compositions as much as possible.

In alternative embodiments, however the present invention also provides polypeptides and pharmaceutical compositions comprising two or more identical or different VHH domains resulting in a bivalent (or multivalent) or a bispecific or (multispecific) polypeptide.

The polypeptides as disclosed herein may at least contain one or more further groups, moieties or residues for binding to other targets or target proteins of interest. It should be clear that such further groups, residues, moieties and/or binding sites may or may not provide further functionality to the amino acid sequences as disclosed herein (and/or to the polypeptide or composition in which it is present) and may or may not modify the properties of the amino acid sequence as disclosed herein. Such groups, residues,
moieties or binding units may also for example be chemical groups which can be biologically and/or pharmacologically active.

These groups, moieties or residues are, in particular embodiments, linked N- or C- terminally to the amino acid sequence as disclosed herein.

It should be noted that the invention is not limited as to the origin of the VHH sequences or functional fragments thereof, polypeptides or compositions of the invention (or of the nucleotide sequences of the invention used to express them). Furthermore, the present invention is also not limited as to the way that the VHH sequences, polypeptides or nucleotide sequences as disclosed herein have been generated or obtained. Thus, the amino acid sequences as disclosed herein may be synthetic or semi-synthetic amino acid sequences, polypeptides or proteins.

The amino acid sequences, polypeptides and compositions provided by the invention can be in essentially isolated form (as defined herein), or alternatively can form part of a polypeptide or composition as disclosed herein, which may comprise or essentially consist of at least one amino acid sequence as disclosed herein and which may optionally further comprise one or more other groups, moieties or residues (all optionally linked via one or more suitable linkers).

In one such aspect, the invention provides a method for identifying new tracer molecules that specifically bind variant 1 of TMEM132D positive cells comprising the steps of:

a) contacting the candidate tracer molecule with a cell-type or cell-line positive for variant 1 of TMEM132D and measure the interaction between the candidate tracer molecule and the cells;

b) contacting the candidate tracer molecule with a cell-type or cell-line negative for variant 1 of TMEM132D and measure the interaction between the candidate tracer molecule and the cells;

c) wherein these candidate tracer molecules that bind the cells of step a) but not the cells of step b) are retained as beta-cell-mass tracer molecules. In a preferred embodiment of said method, the cell-type or cell-line positive for variant 1 of TMEM132D is selected from the group comprising: rodent pancreatic islets, rat INS-1 E cells and the human beta cell line EndoC-BH1 ; and the cell-type or cell-line negative for variant 1 of TMEM132D are PANC-1 or CAPAN-2.

The invention further provides kits for identifying new tracer molecules that specifically bind variant 1 of TMEM132D positive cells comprising two cell types or cell-lines, one being a cell-type or cell-line positive for variant 1 of TMEM132D and one being a cell-type
or cell-line negative for variant 1 of TMEM132D. In a preferred embodiment, the TMEM132D variant 1 positive cell-type or cell-line is selected from the group comprising: rodent pancreatic islets, rat INS-1 E cells and the human beta cell line EndoC-BH1 ; and the TMEM132D variant 1 negative cell-types or cell-lines are PANC-1 or CAPAN-2.

In addition to the use of cell-lines, biochemical binding assays known in the art using the TMEM132D variant 1 biomarker as a target can also be used.

The term "label" includes all suitable isotopic labels for use in PET, PET-CT or SPECT analysis, labels suitable for specific extraction such as magnetic or paramagnetic beads, labels suitable for diagnosis in vitro such as fluorescent dyes or other luminescent labels, known in the art.

The term "beta cell related disorder" described in the methods or uses or kits of the invention encompasses all disorders related to beta cells such as: type 1 diabetes mellitus (T1 D), type 2 diabetes mellitus (T2D), hyperinsulinemia, obesity, neuroendocrine tumors or occurrence of insulinoma.

Additionally, the biomarker of the invention can also be used in in-vitro methods for the analysis of the amount or characteristics of beta cells in a cell culture, either obtained from a biopsy or from a cell-line derived culture. Beta cell specific markers of the invention can further be used to characterize the differentiation state of cells such as modified stem cells, differentiated in vitro as beta cells.

The invention further provides a method for in vivo diagnosis of beta cell deficiency in a subject comprising the steps of:

a) creating an expression matrix by constructing features on a computer from in vivo measurements obtained from a reference pool of healthy subjects, wherein the expression matrix comprises the expression data of the TMEM132D variant 1 biomarker, preferably of variant 1 thereof;

b) storing the expression data of the TMEM132D variant 1 in said reference pool;

c) determining the in vivo expression of TMEM132D variant 1 in the pancreas of the subject to be diagnosed;

e) determining whether there is a deviation of the TMEM132D variant 1 expression in the subject to be diagnosed, compared to the expression of TMEM132D variant 1 in the reference pool of healthy subjects, wherein a decrease in TMEM132D variant 1
expression in the subject as compared to the expression in the reference pool of healthy subjects is indicative for beta cell deficiency.

The invention further provides a method for in vivo diagnosis of beta cell deficiency in a subject comprising the steps of:

a) creating an expression matrix by constructing features on a computer from in vivo measurements obtained from a reference pool of subjects having a condition related to beta cell deficiency, wherein the expression matrix comprises the expression data of the TMEM132D variant I biomarker;

b) storing the expression data of the TMEM132D variant 1 in said reference pool;

c) determining the in vivo expression of TMEM132D variant 1 in the pancreas of the subject to be diagnosed;

e) determining whether there is a deviation of the TMEM132D variant 1 expression in the subject to be diagnosed, compared to the expression of TMEM132D variant 1 in the reference pool of subjects having a condition related to beta cell deficiency, wherein no deviation in TMEM132D variant 1 expression in the subject as compared to the expression in the reference pool of subjects having a condition related to beta cell deficiency is indicative for said beta cell deficiency.

In a further aspect the invention relates to a system comprising:

a computer data repository that comprises a reference value of the quantity of TMEM132D variant 1 in a pool of subjects representing a known diagnosis, prediction and/or prognosis of beta cell deficiency; and

- a computer system programmed to access the data repository and to use information from the data repository in combination with information on the quantity of TMEM132D variant 1 in a subject under diagnosis to make a diagnosis, prediction and/or prognosis of beta cell deficiency in said subject.

Related embodiments of the invention concern a method for making diagnosis, prediction and/or prognosis of beta cell deficiency in a subject comprising:

(i) receiving data representative of values of the in vivo pancreatic quantity of TMEM132D variant 1 from a subject;
(ii) accessing a data repository on a computer, said data repository comprising a reference value of the in vivo pancreatic quantity of TMEM132D variant 1 , said reference value representing a known diagnosis, prediction and/or prognosis of beta cell dysfunction; and

(iii) comparing the data as received in (i) with the reference value in the data repository on the computer, thereby making a diagnosis, prediction and/or prognosis of beta cell dysfunction in the subject.

In certain embodiments, the determination of what action is to be taken, e.g., by a clinician, in view of said diagnosis, prediction and/or prognosis is performed by a (the) computer. In certain embodiments, a (the) computer reports (i.e., generates an electronic report of) the action to be taken, preferably substantially in real time.

In certain embodiments, the invention relates to a method for treating beta cell dysfunction in a subject in need of said treatment, the method comprising the steps of:

(i) in vivo measurement of the quantity of TMEM132D variant 1 in the pancreas of the subject;

(ii) comparing the quantity of TMEM132D variant 1 as measured in (i) with a reference value of the quantity of TMEM132D variant 1 , said reference value representing a known diagnosis, prediction and/or prognosis of beta cell dysfunction;

(iii) finding a deviation or no deviation of the quantity of TMEM132D variant 1 as measured in (i) from the reference value;

(iv) attributing said finding of deviation or no deviation to a particular diagnosis, prediction and/or prognosis of beta cell dysfunction in the subject;

(v) inferring from said particular diagnosis, prediction and/or prognosis of beta cell dysfunction in the subject the presence or absence of a need for a therapeutic or prophylactic treatment of beta cell dysfunction in the subject; and

(vi) subjecting the subject to a therapeutic or prophylactic treatment of beta cell dysfunction when the subject is in need of said treatment.

Illustrative therapeutic and prophylactic treatment of beta cell dysfunction, e.g. diabetes can encompass one or more of the following: the regular administration of insulin, the physiological control of glycemia, the normalization of glycemia, to restore insulin secretion in vivo from cells. Several strategies for said in vivo restoration have been proposed: xenotransplantation of insulin-producing cells from animals, in vitro
differentiation of isolated stem cells into insulin-secreting cells and re-implantation thereof in the patient or allotransplantation of isolated pancreatic islets from another subject.

The pancreas is composed of 1 -2 % of tiny endocrine islets of Langerhans that are scattered in the exocrine tissue. The exocrine pancreas consists of acinar cells and a network of ducts, while the pancreatic islets contain insulin-secreting beta cells and non beta cells, e.g. glucagon-secreting alpha cells, pancreatic polypeptide-producing PP cells, somatostatin-secreting delta cells and ghrelin-secreting epsilon cells. Pancreatic beta cells are selectively destroyed by an autoimmune assault in T1 D, and there is also evidence that beta cell loss is present in long term T2D, albeit at a lower level than in T1 D. Currently there are no methods to estimate beta cell mass and the destruction of beta cells in vivo. To approach this problem we utilized gene expression data on pancreatic islets and purified pancreatic beta cells to identify a beta cell specific target that can be labelled with a tracer in vivo to generate an estimation of beta cell mass. Massively parallel signature sequencing (MPSS) and RNA sequencing (RNAseq) were used to obtain beta cells' and pancreatic islets' gene expression profiles. RNAseq of five independent human pancreatic islet samples, under control condition or following exposure to pro-inflammatory cytokines (i.e. interleukin-1 β + interferon-γ), were also used to evaluate the stability of the transcripts' expression at an inflammatory setting, which is apparent during the pathogenesis of T1 D. This is important, because a transcript and protein inhibited or stimulated by cytokines will reflect a false beta cell mass signal. The human pancreatic islets used for RNAseq were of excellent quality, with a beta cell percentage between 45 and 62% as evaluated by immunofluorescence for insulin, and insulin was at the top of the list of expressed transcripts, with an average level of 19295 RPKM. Islet-enriched transcripts, following the criteria described above, were obtained by comparing the expression levels observed in pancreatic islets to lllumina dataset from 5 human tissues.

A total of 150 genes and 14 transcripts were detected that are relatively specific to pancreatic islets. The genes/transcripts that were significantly (>50%) changed in islets by cytokines were thereafter excluded. Using the Ingenuity Pathway Analysis (IPA) (Qiagen)
we identified 16 genes and 2 transcripts that are islet enriched and located in the cell membrane. For the unknown genes and transcripts we used the TMHMM algorithm to predict their cell location, proteins with transmembrane regions were identified and 9 genes and 1 transcript were retained. The cell localization is an important parameter, as the tracers for in vivo imaging must bind to cell surface proteins. Thereafter was a literature analysis performed of all candidates, and candidates previously identified as auto-antigens were omitted, since endogenous auto-antibodies may interfere with the tracers used for beta cell imaging. The strategy described above is depicted schematically in Figure 1 .

The most interesting transcript found using this method is encoding for variant 1 of the TMEM132D protein (Figure 2). There are currently three known splice variants described for TMEM132D, but the variant 3 is labelled as a preliminary sequence (EnsembI). The variant 2 has a small extracellular part and is therefore most likely not expressed on the cell surface, while variants 1 and 3 have a large extracellular part which serves a good target for tracers. The difference between variant 1 and 3 is that the version 3 misses the last 20 amino acids in the signalling peptide region.

Example 2: Validation of the islet specific expression of the selected biomarker

To validate the specificity of the identified transcript, mRNA expression of TMEM132D variant 1 and 2 were quantified in different human tissues, cell lines and human islets (HI) (Figure 3). Three different human islet preparations were used for the analysis as well as two cell lines: Capan-2, human pancreatic ductal adenocarcinoma cells and panc-1 , human exocrine pancreas carcinoma cells. The primers used for the variant 1 were HTME1 RTForward (SEQ ID NO: 9) and HTME1 RTReverse (SEQ ID NO: 10). The primers used for the variant 2 were HTME2RTForward (SEQ ID NO: 1 1 ) and HTM E2RT reverse (SEQ ID NO: 12). Variant 1 showed the most selective expression as it had the highest expression in HI and very limited expression in the other tissues. To evaluate protein expression and the intra-pancreatic localization in mouse pancreas, we used a commercial antibody (anti-TMEM132D antibody, Abeam ab1 16041 ; Figures 4-6). In Figure 4, the darker brown staining (cf. circles) represents the TMEM132D staining, and the darker blue dots are the nuclei of the cells. Immunofluorescence cytochemistry of Insulin, Glucagon, TMEM132D and Hoechst DNA staining in rat pancreas was also performed on the same tissue section in order to show the overlap of TMEM132D staining with insulin- producing beta cells (Figure 5). Figure 6 shows staining of human pancreas for insulin and TMEM132D.
Example 3: Identification of Nanobodies (Nbs) specifically binding to TMEM132D variant 1

In a next step, binding molecules that specifically bind with TMEM132D-variant-1 -positive cells were identified. Such molecules can be used as tracers for visualizing beta-cell mass. An approach to this is to utilize camelid single-domain antibody-fragment ("Nanobodies" (Ablynx NV), further referred to herein as "Nb(s)") libraries, which could be screened for nanobodies that specifically bind to variant 1 of the TMEM132D protein.

The development of cross-reactive Nbs is crucial for a straightforward preclinical validation of the marker and development of an imaging tracer. Therefore, it was decided that in the development of Nbs targeting TMEM132D variant 1 , the immunization, panning and screening had to be performed with both the human and mouse orthologs of the extracellular domain of the protein (h-TMEM132D variant 1 and its mouse orthologue m- TMEM132D).

The predicted presence of a large extracellular domain makes TMEM132D variant 1 a suitable candidate for the standardized Nb development procedure. This Nb development procedure requires recombinant protein of the target's extracellular domain for the immunization of a camelid, the bio-panning by phage display and the in vitro screening and characterization of the isolated Nbs. Since no recombinant protein was commercially available at the time of target selection, the recombinant protein development was initiated in-house. Plasmids encoding the human or the mouse ortholog of TMEM132D were obtained from Origene (RG223905 (human) and MG218440 (mouse)) and the extracellular domain of both proteins was recloned into an expression vector suitable for recombinant protein production in a mammalian expression system (pES31 vector: Schoonooghe et al., 2009, BMC Biotechnology 9:70, doi: 10.1 186/1472-6750-9-70). In this expression vector, the cloning site is under the control of a strong constitutive promotor (3actin-3globulin promoter with CMV enhancer) with a signal sequence for secretion of the protein into the culture medium (consensus excretion signal sequence MGWSCIIFFLVATATGVHS (SEQ ID NO: 2)).

The extracellular domain of the protein was amplified by PCR using a proof-reading DNA polymerase (Vent polymerase) with primers SMM21 and SMM22 for h-TMEM132D variant 1 and SMM04 and SMM05 for m-TMEM132D (Table 1 ). The sense primers SMM21 and SMM04 introduce a 5'-terminus Nhel restriction site, and the anti-sense primers SMM22 and SMM05 introduce a C-terminal hexahistidine tag for purification, followed by a double stop codon and a Hindi 11 restriction site at the 3'-terminus.
Table 1 - Primers

Primer Sequence (5' -> 3') #

SMM21 AAAAGCTAGCCGAGGGATCCTTGAGAGCATCC SEQ ID NO: 3

SMM22 TTTTAAGCTTCTATTAGTGATGGTGATGGTGGTGGTC SEQ ID NO: 4

GCTCAGCCC I I I GGATGCC

SMM04 AAAAGCTAGCCGAGGGATCCTGGAGAGCATTC SEQ ID NO: 5

SMM05 TTTAAGCTTCTATTAGTGATGGTGATGGTGGTGGTCA SEQ ID NO: 6

CTCAGCCCCTTGGCTG

HTME1 RTForward CGGGAGCATCTTCCTTTATC SEQ ID NO: 9

HTME1 RTReverse TTTCCTCACG GTCTTTG GTATA SEQ ID NO: 10

HTME2RTForward CTCAGAGAGCACCTTTCATAACA SEQ ID NO: 1 1

HTME2RTreverse GGGAGGAGGTCCTGGTATG SEQ ID NO: 12

The PCR fragments were digested with Nhel and Hindlll and ligated into the pES31 expression vector. The redoning was confirmed by DNA sequencing. Translation of the DNA sequence and the cleavage of the signal sequence after secretion results in the following protein sequences being secreted by the producing cells:

The C-terminal His-tagged extracellular domain of variant 1 of TMEM132D (for both the human and mouse ortholog) was produced from the above constructed pES31 plasmids by the Protein Service Facility (Flemish Institute of Biotechnology, VIB). In short, HEK293T cells were transiently transfected. After diafiltration of the culture medium, the recombinant protein was purified via immobilized metal affinity chromatography (I MAC) and subsequent size-exclusion chromatography (SEC).

Prior to immunization of a camelid, the recombinant proteins were analyzed by SDS- PAGE. Both the human and mouse orthologs could be seen as a band of ca. 130 kDa, which probably corresponds to the extracellular domain (99 kDa) + glycosylation (Nomoto et al., 2003, J. Biochem. 134, pp. 231 -238, DOI: 10.1093/jb/mvg135). The protein was positively identified by Western blot with the commercial rabbit anti-TMEM132D polyclonal antibody (Abeam Ab1 16041 ).
Two alpacas were immunized with the generated recombinant proteins. We chose to immunize two animals in order to increase the chance of finding an appropriate binder for use in beta cell mass imaging. Furthermore an alternating immunization scheme (with human and mouse recombinant protein) was used to boost generation of cross-reactive Nbs. Two independent immune nanobody phage display libraries were generated. The two obtained libraries were enriched for specific binders by panning via phage-display on recombinant protein. The panning of both libraries was performed in parallel; however the phages of both libraries were kept apart. The panning was performed in subsequent rounds on solely the mouse ortholog (three rounds), solely the human ortholog (two rounds) or species-alternating (two rounds, human-mouse).

3.1 Identification of genuine anti-TMEM132D variant 1 Nanobodies

From the different panning rounds Nb-containing periplasmic extracts (PEs) from 752 randomly chosen clones were screened in an enzyme-linked immunosorbent assay (ELISA) assay on recombinant protein. Mouse-anti-HA monoclonal antibody was used to detect the HA-tag of the Nb, and the secondary antibody was an anti-mouse-alkaline phosphatase conjugate. The ELISA was developed with phosphatase substrate.

The PE-ELISA retained 263 clones that were binding the mouse and/or human ortholog specifically (representative clones are shown in Table 2), which is defined as the signal in an Ag-coated well that is at least twice the signal in a control well not coated with Ag. These Nbs could be divided into 25 different groups based on the sequence homology of the CDR 3 loop.

Table 2. Nb-containing PE screening via ELISA and flow cytometry.

During panning Nb clones are screened on recombinant mouse and human TMEM132D variant 1 proteins in a PE-ELISA assay. A signal-to-background ratio (antigen-coated versus uncoated well) greater than 2 is considered as specific binding { ). Nbs are grouped according to sequence homology of CDR3. Per group selected Nbs were tested for binding mouse and human TMEM132D-variant-1 -transfected CHO cells. A difference in mean fluorescence intensity (Δ mfi) smaller than 10 in comparison to a control without Nb is considered as a false binder (*).

In a second screening step, recognition of the receptor in its natural conformation was verified via flow cytometry on CHO cells stably transfected with TMEM132D variant 1 (Table 2) with Nb-containing PE. In this assay, HA-tagged Nb binding to cells was visualised by the subsequent addition of anti-HA antibody and secondary fluorescent anti- mouse lgG1 antibody. For each Nb group the PE of at least one representative clone was tested. Five groups did not bind the transfected cells and were excluded.

3.2 In vitro and in vivo characteristics of selected purified Nanobodies

Six Nanobodies were selected and produced for further characterization: 50T91 , 49T130, 49T150, 50T180, 49T191 and 49T247. These clones were selected based on their genuine recognition of mouse TMEM132D variant 1 and possible cross-reactivity to the human orthologue (Table 2).

The six selected Nbs were recloned into the pHEN6 expression vector, to add a C- terminal His-tag to the Nb, and produced in an E. coli expression system. The production yield obtained after IMAC and SEC purification was greater than 1 mg/L bacterial culture for all Nbs (Table 3).

The kinetic parameters of TMEM132D-variant-1 -binding Nbs were determined for both species orthologs via surface plasmon resonance on immobilized recombinant proteins and using different concentrations of Nbs as analytes (Table 3). For Nb 50T180 no binding
was observed. All other Nbs bound with nanomolar affinity to both mouse and human proteins. Distinct kinetic patterns with for example slow association and dissociation (Nb 49T150), or fast association and dissociation (Nb 49T130) were observed.

Also, thermal stabilities of purified Nbs were determined by the Thermofluor method (Ericsson et al., 2006, Analytical Biochemistry 357, pp 289-298, DOI:10.1016/j.ab.2006.07.027) and are shown in Table 3. In this assay, Nb is mixed with SYPRO Orange dye (Thermo Fisher Scientific) and samples were measured in triplicate in a real-time PCR detection system (Bio-Rad). The temperature of the samples was raised at 0.5°C/min until 95°C was reached. Upon protein unfolding the SYPRO dye binds to the exposed hydrophobic regions in the Nb and fluoresces. The Tm value is the value at which half of the protein is unfolded.

Next, the candidates' in vivo properties were evaluated by biodistribution studies in normal mice (Figure 7). To this extent the Nbs were radiolabeled with 99mTc via tricarbonyl chemistry on their His-tag (Xavier et al., 2012, Methods Mol. Biol. 91 1 , pp 485-490, DOI: 10.1007/978-1 -61779-968-6_30). The ex vivo biodistribution analysis at 90 min post- injection of the TMEM132D-targeting Nbs showed overall no important differences with the non-targeting control Nb BclM O (Conrath et al., 2001 , Antimicrob. Agents Chemother 45, pp 2807-2812, DOI 10.1 128/aac.45.10.2807-2812.2001 ) (Figure 7).This Nb BclM O, targeting bacterial beta-lactamase, is included as a measure for unspecific uptake of the 99mTc-radiolabeled Nbs in the different tissues. The Nbs were eliminated fast from the blood, which allows examination at time points early after injection of the radiotracer and is necessary to generate sufficient contrast for beta cell imaging, and a low uptake was observed in all organs except kidneys, which was anticipated since we aimed for a targeting agent with a specific uptake in the pancreatic beta cells and low or no uptake in other tissues. The kidneys are the major elimination route of low molecular weight tracers (< 60 kDa), which resulted in a high retention that varied between 75.58% ± 2.66% lA/g and 296.1 1 % ± 8.29% lA/g and was Nb dependent. Nb 49T130 also showed a minor elevated liver uptake.

Since all 6 Nbs passed the in vivo evaluation in normal mice, three Nbs (50T91 , 49T130 and 49T150) were selected based on their highest affinity for the human ortholog of the recombinant protein (Table 3) for further evaluation of their binding capacity to the TMEM132D receptor. The three selected candidates were evaluated in vivo in mice that were xenografted subcutaneously with h-TMEM132Dv1 overexpressing CHO tumors (Right hind leg: untransfected CHO cells and left hind leg: h-TMEM132Dv1 transfected CHO cells).
After radiolabeling Nbs 50T91 , 49T130, 49T150 and Bell 10 with 99mTc, SPECT-CT imaging was performed at 1 h post-injection. All three TMEM132D-targeting Nbs clearly visualized the TMEM132D tumor with high contrast, while no uptake was seen in the control tumor. On the contrary the non-targeting control Nb Bell 10 did not accumulate in the TMEM132D tumor. For all Nbs the kidneys and bladder were visible, as a result of the typical body elimination route of radiolabeled Nbs. For Nb 49T130 also some liver uptake was observed, which corresponds with the previous result in normal C57BL/6 mice. These results were confirmed in the ex vivo biodistribution analysis at 90 min post-injection (Table 4). The high TMEM132D tumor-to-blood and TMEM132D tumor-to-muscle values for TMEM132D-targeting Nbs, in comparison to the ratios for the control tumor and the values for the non-targeting control Nb BclM O, demonstrate the specificity for the receptor and the suitability of the Nbs as imaging tracers.

Table 3. In vitro characterization of purified Nbs.

Mouse TMEM132D Human TMEM132D

Productio ka KD ka KD

kd Chi2 kd Chi2 Tm

Clone n yield

(M'1 (x109 (M'1 (x109

RU2)

(mg/L) is"1) (

M) is"1) (RU2) (°C)

M)

5.1 1.5 2.3 2.8

50T91 4.9 2.9 0.12 1.2 1.06 62 x106 x10"2 x106 x10"3

5.3 4.1 4.6 7.2

49T130 6.2 7.7 0.05 1.6 0.87 52 x106 x10"2 x106 x10"3

1.6 2.3 2.0 2.9

49T150 6.9 1.4 0.08 1.4 0.40 78 x105 x10"4 x105 x10"4

a a

50T180 6.3 82

5.6 3.9 2.5 5.5

49T191 1.3 6.9 0.05 21.7 0.36 64 x105 x10"3 x105 x10"3

5.8 1.5 3.2 2.3

49T247 3.3 2.6 0.04 7.2 0.68 64 x105 x10"3 x105 x10"3

Kinetic parameters were determined via SPR on immobilized mouse or human TMEM132D recombinant protein. The Nb clones selected for evaluation of the in vivo targeting capacity are shown in bold.

b) visualizing the labelled molecule specifically located to the beta cell population in the pancreas in vivo,

c) quantifying the beta cells mass in said subject,

d) comparing the beta cell mass data obtained in step c) with the beta cell mass of a healthy subject, or of a previous analysis of the same subject.

e) diagnosing the subject as having diabetes or being at risk of having diabetes when the level of beta cell mass obtained in step c) is reduced as compared to that of a healthy subject and diagnosing the subject as having hyperinsulinemia or being at risk of having hyperinsulinemia when the level of beta cell mass obtained in step c) is increased as compared to that of a healthy subject, or of a previous analysis of the same subject.

1 1 . The method according to claim 10, wherein said labelled molecule is selected from the group comprising: an antibody or a fragment thereof, a nanobody, an affibody, a minibody, a diabody, a single chain antibody, an aptamer, a photoaptamer, a peptide, a small molecule, an interacting partner, an isotopically labelled tracer, or a ligand, specifically binding to TMEM132D variant 1 .

12. The method according to claim 10 or 1 1 , wherein said in vivo visualisation is done using a PET, PET-CT, SPECT or MRI scan, or through fluorescent imaging.

13. The method of any of the claims 10 to 12, wherein the beta-cell-related disorder is type 1 diabetes mellitus, type 2 diabetes mellitus, hyperinsulinemia, obesity, or occurrence of insulinoma.

14. A labelled molecule, specifically binding to TMEM132D variant 1 , for use in

diagnosis of a beta-cell-related disorder in vivo, according to the method of any one of claims 10 to 13, preferably wherein the beta-cell-related disorder is type 1 diabetes mellitus, type 2 diabetes mellitus, hyperinsulinemia, obesity, or occurrence of insulinoma.

15. A kit for visualising beta cells, for specifically measuring beta cell-mass, for

diagnosing a beta-cell-related disorder, for detecting beta cell fragments in a blood or urine sample, and/or for purifying beta cells in a subject comprising a labelled molecule specifically binding to TMEM132D variant 1 , preferably wherein said binding molecule is an antibody or a fragment thereof, a nanobody, an affibody, a minibody, a diabody, a single chain antibody, an aptamer, a photoaptamer, a peptide, a small molecule, an interacting partner, an isotopically labelled tracer, or a ligand, specifically binding to TMEM132D variant 1 .

16. The method use or kit of any of the previous claims, wherein the binding molecule is a nanobody.

17. A method for following up the success of the transplantation of beta cells in a

subject comprising the following steps:

a) measuring the amount of beta-cell mass in the subject at one or more time points after transplantation of the subject with beta cells with the method according to claim 5,

b) determining the success of the transplantation by comparing the beta cell mass in the course of time by evaluating the evolution of beta-cell mass over time.

18. A method for purifying or isolating beta cells from other pancreatic non-beta cells comprising the following steps:

b) isolating the labelled cells from the non-labelled cells through the tag on the beta cells, thereby obtaining a substantially pure beta cell preparation.

19. A method for identification of regeneration of beta cells comprising the steps of: a) tagging the beta cells with a labelled binding molecule specifically binding to variant 1 of TMEM132D,

b) isolating the labelled cells from the non-labelled cells through the tag on the beta cells, thereby obtaining a substantially pure regenerated beta cell preparation c) performing immunohistochemistry to identify the number of newly regenerated beta cells, and to define the new beta cell mass

c) performing immunohistochemistry to identify the number of precursor beta
cells, and optionally to define the new beta cell mass; and/or d) following-up op therapeutic strategies and detect newly formed beta

cells.

23. A method for identifying new tracer molecules that specifically bind beta cells

comprising the steps of:

a) contacting the candidate tracer molecule with TMEM132D variant 1 positive cells or cell-lines and measure the interaction between the candidate tracer molecule and the cells;

b) contacting the candidate tracer molecule with TMEM132D variant 1 negative cells or cell-lines and measure the interaction between the candidate tracer molecule and the cells;

c) comparing the interactions between both steps a) and b); and

d) retain these candidate tracer molecules that bind the cells of step a) but not the cells of step b) as beta-cell-mass tracer molecules.

24. The method of claim 23, wherein the TMEM132D variant 1 positive cell or cell-line is selected from the group comprising: rodent pancreatic islets, rat INS-1 E cells and the human beta cell line ENDOC-BH1 ; and wherein the TMEM132D variant 1 negative cell-types or cell-lines are PANC-1 or CAPAN-2.

25. A kit for identifying new tracer molecules that specifically bind beta cells comprising two cell types or cell-lines, one being a TMEM132D variant 1 positive cell-type or cell-line and one being a TMEM132D variant 1 negative cell-type or cell-line.

28. A binding molecule specifically binding TMEM132D variant 1 , preferably selected from the group comprising: an antibody or a fragment thereof, a nanobody, an affibody, a minibody, a diabody,, a single chain antibody, an aptamer, a

photoaptamer, a peptide, a small molecule, an interacting partner, an isotopically labelled tracer, or a ligand specifically binding to TMEM132D, preferably to variant 1 of TMEM132D.

29. The binding molecule according to claim 28, which is a nanobody.

30. Use of the binding molecule according to claim 28 or 29, or of the kit according to any one of claims 25 or 26, for delivering therapeutic agents specifically to beta cells, with the goal of protecting these cells against dysfunction and death in diabetes.

31 . A kit comprising binding molecules according to aspect 28 or 29.

32. The kit according to claim 31 , wherein said binding molecules are immobilised on a solid support, such as beads, a chip or a microchip.

33. The kit according to claim 31 or 32, wherein said binding molecules are labelled, preferably with a radioisotope, a fluoresecent moiety, a chemiluminescent moiety, a bioluminescent moiety, a chemifluorescent moiety or a metal or magnetic moiety.

34. The kit according to any one of claims 31 to 33, comprising one or more

35. A method of diagnosing T1 D using the binding molecule according to any one of claims 28 or 29, or the kit according to any one of claims 31 to 34, comprising detection of beta cells and/or beta cell debris in the circulation of a subject, wherein such detection is indicative of T1 D disease development.

36. A method of diagnosing T1 D using the binding molecule according to any one of claims 28 to 29, or the kit according to any one of claims 31 to 34, comprising detection of beta cells and/or beta cell debris in the circulation of a subject, wherein an increase in detection of beta cells and/or beta cell debris over time in the circulation of the subject is a measure for disease progression.

37. A method of diagnosing T1 D using the binding molecule according to any one of claims 28 or 29, or the kit according to any one of claims 31 to 34, comprising detection of beta cells and/or beta cell debris in the circulation of a subject, wherein
a decrease in detection of beta cells and/or beta cell debris over time is a measure for disease improvement and hence of successful treatment.

38. A method of monitoring beta cell transplants in the skin intramuscular, or in other accessible locations of the subject using the binding molecule according to claim 28 or 29, or the kit according to any one of claims 31 to 34, comprising the detection of the labelled binding molecule(s) specific for beta cells, preferably fluorescently labelled binding molecules, using non-invasive clinical imaging methods.